Research ArticleDiversity and Multiplexing Technologies by 3D Beams inPolarized Massive MIMO Systems

Xin Su1 and KyungHi Chang2

1College of Internet of Things (IOT) Engineering Hohai University Changzhou 213022 China2Electronic Engineering Department Inha University Incheon 402751 Republic of Korea

Correspondence should be addressed to KyungHi Chang khchanginhaackr

Received 13 July 2015 Revised 14 November 2015 Accepted 29 November 2015

Academic Editor Jing Liang

Copyright copy 2016 X Su and K ChangThis is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Massive multiple input multiple output (M-MIMO) technologies have been proposed to scale up data rates reaching gigabits persecond in the forthcoming 5G mobile communications systems However one of crucial constraints is a dimension in space toimplement theM-MIMO To cope with the space constraint and to utilize more flexibility in 3D beamforming (3D-BF) we proposeantenna polarization in M-MIMO systems In this paper we design a polarized M-MIMO (PM-MIMO) system associated with3D-BF applications where the system architectures for diversity and multiplexing technologies achieved by polarized 3D beamsare provided Different from the conventional 3D-BF achieved by planar M-MIMO technology to control the downtilted beam ina vertical domain the proposed PM-MIMO realizes 3D-BF via the linear combination of polarized beams In addition an effectivearray selection scheme is proposed to optimize the beam-width and to enhance system performance by the exploration of diversityand multiplexing gains and a blind channel estimation (BCE) approach is also proposed to avoid pilot contamination in PM-MIMO Based on the Long Term Evolution-Advanced (LTE-A) specification the simulation results finally confirm the validity ofour proposals

1 Introduction

Massive multiple input multiple output (M-MIMO) is beingdeveloped as a promising technology for several attractivefeatures [1ndash3] for example the system capacity can be the-oretically increased by installing sufficient antennae and thetransmit power can potentially be reduced in inverse propor-tional to the square root of the number of applied antennae [45]This not only is relevant from a commercial standpoint butalso provides green transmission to address health concernsin wireless communications [6] When channel reciprocity isexploited in time division duplex (TDD) M-MIMO systemsthe overhead related to channel compensation scales linearlyonly with the number of mobile user-equipment (UE) percell rather than the number of antennae per base station (BS)[7] Matched filtering is suggested as being optimal for linearprecoders and detectors because thermal noise interferenceand channel estimation errors can theoretically vanish in M-MIMO systems [1] The remaining performance limitation is

the pilot contamination [8] which is the residual interferencecaused by the reuse of pilot patterns The above claims arevalidated based on several crucial but optimistic assumptionsof perfect channel estimation hardware implementationsand the number of antennae applied in practice Recently alot of the literature has studied M-MIMO with more realisticassumptions [9ndash13]

On the other hand there has been a gradual demand forthe use of polarized antenna systems especially for 5Gmobilecommunications systems [14ndash16] This is mainly because theantenna polarization is a pivotal resource to be exploited forthe design of space-limited wireless devices Techniques suchas space-time diversity multiplexing and array processingcan be applied to polarized antenna systems to boost systemthroughput

In this paper we propose a polarized M-MIMO (PM-MIMO) array system where three orthogonally colocatedantenna branches are applied at each array element (AE) of anM-MIMOsystemThree-dimensional beamforming (3D-BF)

Hindawi Publishing CorporationMobile Information SystemsVolume 2016 Article ID 2318287 15 pageshttpdxdoiorg10115520162318287

2 Mobile Information Systems

can be realized by the proposed PM-MIMO system and thegenerated beams can be steered and varied at119883-119884119883-119885 and119884-119885 planes respectivelyThe system architectures of diversityand multiplexing schemes achieved by polarized 3D beamsare provided based on the proposed PM-MIMOarray systemA robust array selection scheme for 3D-BF applications isadditionally proposed to efficiently optimize the beam-widthand to enhance system performance by the exploration ofdiversity and multiplexing gains

Normally in M-MIMO systems when the number of BSantennae grows large the size of M-MIMO channel matrixgrows largeThe vector ofM-MIMO channelmatrix becomesvery long and any two of them are pairwise orthogonalHowever in a space-limited system pairwise orthogonalitycannot be maintained because the adjacent AE space isusually set equal to or to less than a half signal wave-length Therefore for this paper we additionally modifieda conventional blind channel estimation (BCE) approach toexploit the pairwise orthogonality according to the particularcharacteristics of PM-MIMO systems That is the polarizedcross-branch links in the system are usually uncorrelated [17]The proposed BCE approach is presented for PM-MIMO toavoid the pilot contamination and to enhance the systemspectrum efficiency By applying our proposals under thepolarized MIMO channel model Monte Carlo simulationsfinally confirm the validity of our proposals

The remaining parts of this paper are organized asfollows Section 2 describes the proposed PM-MIMO arraysystem and the proposed AE selection scheme is providedin Section 3 In Section 4 a BCE approach for PM-MIMO isintroduced and the simulation results are demonstrated anddiscussed in Section 5 Finally our conclusions are drawn inSection 6

2 PM-MIMO Array System

Figure 1 provides an example of a uniform linear array (ULA)with antenna polarization in the array and branch (AampB)multiple antennae configuration where three orthogonallycolocated antenna branches are fixed at each AE (ie antennaport) The beam-width is proved to be relevant to array con-figuration where it is inversely proportional to the numberof AEs and array element spacing Because the spacing ofthree colocated branches at each AE is set to zero as shownin Figure 1 which makes beam-width scale up to 360∘ thebeams should be generated via corresponding cross-arraybranches rather than the colocated branches at each AE [16]Therefore we can obtain three orthogonal beams generatedby a polarized ULA as follows

(i) Beam steered in 119883-119884 plane is generated by thebranches set of 119860

1199011198611 where 119901 is the index of AE

(ii) Beam steered in 119883-119885 plane is generated by thebranches set of 119860

1199011198612

(iii) Beam steered in 119884-119885 plane is generated by thebranches set of 119860

1199011198613

Let 1198751198611

(120579 120601 12057901

) 1198751198612

(120579 120601 12057902

) and 1198751198613

(120579 120601 12057903

)

represent the beam radiation patterns generated by the

Z

XY

A1B1 A2B1

A2B3A1B3

A1B2 A2B2

middot middot middot middot middot middot

ApB2

ApB3

ApB1

Array elementAntenna branch

Figure 1 Uniform linear array with antenna polarization

above three sets 1198601199011198611 119860

1199011198612 and 119860

1199011198613 respectively We

have

1198751198611

(120579 120601 12057901

) =

119873

sum

119899=1

119890119895(119899minus1)(2120587120576)(sin 120579minussin 120579

01)

=sin ((120587119873120576) (sin 120579 minus sin 120579

01))

119873 sdot sin ((120587120576) (sin 120579 minus sin 12057901

))

(1)

1198751198612

(120579 120601 12057902

) =

119873

sum

119899=1

119890119895(119899minus1)(2120587120576)(sin 120601minussin 120579

02)

=sin ((120587119873120576) (sin120601 minus sin 120579

02))

119873 sdot sin ((120587120576) (sin120601 minus sin 12057902

))

(2)

1198751198613

(120579 120601 12057903

) =

119873

sum

119899=1

119890119895(119899minus1)(2120587120576)(sin(1205872minus120601)minussin 120579

03)

=sin ((120587119873120576) (cos120601 minus sin 120579

03))

119873 sdot sin ((120587120576) (cos120601 minus sin 12057903

))

(3)

where 120579 and 120601 denote the azimuth and elevation angle ofthe radiation pattern 120576 is the array element spacing factordefined by [16] and 120579

01 120579

02 and 120579

03are the off bore-sight

angles corresponding to1198601199011198611119860

1199011198612 and119860

1199011198613 respectively

[16] Figure 2(a) with 119873 = 8 then depicts the 3D beamsgenerated by a triple polarized ULA (TPULA) system via (1)(2) and (3) where three orthogonal beams can be steered andvaried separately on the 119883-119884 119885-119883 and 119884-119885 planes For thesecond subfigure of Figure 2(a) 120579

01 120579

02 and 120579

03are set as

30∘ According to Figure 2(b) a very narrow beam-width isobtained by applying a large number ofAEs for example119873 =

64 AEs that performs quite well in terms of BF interferencesmitigation

By employing the TPULA at each multiplexer (MUX)the structure of our proposed PM-MIMO array systemis illustrated in Figure 3 with the received signal being givenas

119910 =

119876

sum

119902=1

3

sum

119887=1

(119908119901119887119902

ℎ119901119887119902

119909119901119887119902

+ 119899119901119887119902

) (4)

where ℎ119901119887119902

is the subpolarized channel corresponding to119876th 119860

119901119861119887array element 119908

119901119887119902denotes the 3D-BF weights

multiplied at each antenna branch and 119901 (1 2 119875) 119887

(1 2 3) and 119902 (1 2 119876) represent the AE index branch

Mobile Information Systems 3

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus1

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus11

050

minus05minus1 1

050minus05

minus1

minus1 minus05 0 051 minus1minus050051

XX

ZZ

YY

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus11

Z

(a) 3D beams generated by a triple-polarized ULA system

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus1

1080604020minus02minus04minus06minus08minus11080604020minus02minus04minus06minus08minus11

08

06

04

02

0

minus02

minus04

minus06

minus08

minus1

X X

YY

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus1

Y

BW8 BW64

(b) Beam-width varied with different number of AEs being employed for example 8 and 64 AEs

Figure 2 3D beams generated by a polarized ULA

index andMUX index respectivelyThe 3D-BF which can beapplied for multipath reception or combination of relay sig-nals [18] is introduced as a promising technique inM-MIMOsystems to enhance the cellular performance by deployingantenna elements in both horizontal and vertical (HampV)dimensions [19] However different from the conventional3D-BF achieved by planar M-MIMO system to control thedowntilted beam in a vertical domain the proposed PM-MIMO realizes the 3D-BF via the linear combination ofpolarized beams It highlights the fact that the 3D-BF not onlyis addressed by theHampV exploration but also can be achievedby antenna polarizationmeanwhile the antenna polarizationalso serves as a pivotal solution dedicated to space constraintin M-MIMO systems

3 Diversity and MultiplexingAchieved by Polarized 3D Beams withan Array Selection Scheme

31 System Architecture Figure 4 describes the architectureof the proposed diversity system via polarized 3D beamswhere the multiple users with each equipping three colocatedantenna branches are considered As studied by Dao et al[17] the cross-array links (eg from BS 119860

11198611and 119860

21198611

to UE 1198611) can be highly correlated by setting the AE

space equal to or less than a half-wavelength The cross-branch links (eg from BS 119860

11198611and 119860

11198612to UE 119861

1) on

the other hand are usually uncorrelated due to the spacepolarizationThis inspired us to incorporate space-time block

4 Mobile Information Systems

MUX-Q

A1B2

A1B1

A1B3

A2B2

A2B3A2B1

APB2

APB1

APB3

MUX-1MUX-2

sQ(t)

X

Y

w12q(t)

w13q(t)

w11q(t)

w22q(t)

w23q(t)

w21q(t)

wP2q(t)

wP3q(t)

wP1q(t)

s2(t)s1(t) S(t)

Figure 3 Structure of the proposed PM-MIMO array system

coding (STBC) and BF techniques simultaneously in theTPULA system to boost performance Moreover in orderto achieve full-rate coding with an odd number of transmitantennae quasi-orthogonal STBC (QO-STBC) has emergedin the literature [20 21] which fully explores diversity gainbut increases the complexity of decoding due to nonorthog-onal interference In this paper the proposed diversityscheme combines QO-STBC for three transmit antennaeand BF techniques via the TPULA system as illustrated inFigure 4

In Figure 4 the BF weights (119908Tx119901119887

) are multiplied beforethe inverse fast Fourier transform (IFFT) block of the BSX

119901in (5) is the transmitted QO-STBC symbol matrix [20]

X119901= (

119909II 119909III 119909IV

119909lowast

I minus119909lowast

IV 119909lowast

III

119909IV 119909I 119909II

119909lowast

III minus119909lowast

II 119909lowast

I

)

119868-by-119869

(5)

where the Roman numeral is the symbol index 119894 is the timeindexmodulo of 4 (119868 = 4) and 119895 is the antenna indexmoduloof 3 (119869 = 3) At each UE the QO-STBC decoding is appliedafter the FFT block at each antenna branch [20] and then we

can have the received signal for each branch of a specific UEbefore QO-STBC decoding as

R119901sim119894thUE

119887

= (h119901sim119894thUE

119887

(WTx119901sim119894thUE

119887

⊙ X119901sim119894thUE

119887

)119879

)

119879

+ n119901sim119894thUE

119887

= (WTx119901sim119894thUE

119887

⊙ X119901sim119894thUE

119887

) h119879119901sim119894thUE

119887

+ n119901sim119894thUE

119887

= (119903119901sim119894thUE

119887I 119903

119901sim119894thUE119887II 119903

119901sim119894thUE119887III 119903

119901sim119894thUE119887IV)

119879

(6)

where ldquo⊙rdquo denotes the Hadamard product and WTx119901

is theTxBF weighting matrix given by

WTx119901sim119894thUE

119887

= (

119908Tx1199011

119908Tx1199012

119908Tx1199013

119908Tx1199011

119908Tx1199012

119908Tx1199013

119908Tx1199011

119908Tx1199012

119908Tx1199013

119908Tx1199011

119908Tx1199012

119908Tx1199013

) (7)

h119901sim119894thUE

119887

is the vector of the polarized cross-branch linksgiven by

h119901sim119894thUE

119887

= (ℎ1199011sim119894thUE

119887

ℎ1199012sim119894thUE

119887

ℎ1199013sim119894thUE

119887) (8)

Mobile Information Systems 5

QO-STBCdecoding

QO-STBCdecoding

QO-STBCdecoding

IFFT and GI extension

GI removal

1st UE

A1B2

A1B1

A1B3

A2B2A2B3

A2B1

A3B2A3B3

A3B1

and FFT

B1

B2

Y

X

qth MUX ofPM-MIMO

APminus2B3

APminus2B2

APminus2B1

APminus1B2

APminus1B1

APminus1B3

APB3

APB2

APB1

wTx12

wTx13

wTx11

wTx22

wTx23

wTx21

wTx32

wTx33

wTx31

wTxP2

wTxP3

wTxP1

wTx(pminus2)2

wTx(pminus2)3

wTx(pminus2)1

wTx(pminus1)2

wTx(pminus1)3

wTx(pminus1)1

B3

B3

B2

B1

Kth UE

EGC

EGC

QO-STBC

QO-STBC

QO-STBCdecoding

QO-STBCdecoding

QO-STBCdecoding

Figure 4 Diversity system architecture by polarized 3D beams

and n119901sim119894thUE

119887

is the noise vector given by

n119901sim119894thUE

119887

= (120590119901sim119894thUE

119887I 120590

119901sim119894thUE119887II 120590

119901sim119894thUE119887III 120590

119901sim119894thUE119887IV)

119879

(9)

The STBC decoding applied thereafter gives

X119901sim119894thUE

119887

= D119901sim119894thUE

119887

Τ119901sim119894thUE

119887

= (119901sim119894thUE

119887I

119901sim119894thUE119887II

119901sim119894thUE119887III

119901sim119894thUE119887IV)

119879

(10)

Here D119901sim119902119887

is the STBC decoding matrix which is modifiedbased on equation (12) in [20] by considering TxBF weights

D119901sim119894thUE

119887

=

((((

(

0 119908Tx1199011

ℎ1199011sim119894thUE

119887

(119908Tx1199012

)lowast

ℎlowast

1199012sim119894thUE

119887

119908Tx1199013

ℎ1199013sim119894thUE

119887

(119908Tx1199011

)lowast

ℎlowast

1199011sim119894thUE

119887

0 (119908Tx1199013

)lowast

ℎlowast

1199013sim119894thUE

119887

minus119908Tx1199012

ℎ1199012sim119894thUE

119887

(119908Tx1199012

)lowast

ℎlowast

1199012sim119894thUE

119887

119908Tx1199013

ℎ1199013sim119894thUE

119887

0 119908Tx1199011

ℎ1199011sim119894thUE

119887

(119908Tx1199013

)lowast

ℎlowast

1199013sim119894thUE

119887

minus119908Tx1199012

ℎ1199012sim119894thUE

119887

(119908Tx1199011

)lowast

ℎlowast

1199011sim119894thUE

119887

0

))))

)

(11)

6 Mobile Information Systems

where Τ119901sim119902119887

is defined as

Τ119901sim119894thUE

119887

= (119901sim119894thUE

119887I

lowast

119901sim119894thUE119887II

119901sim119894thUE119887III

lowast

119901sim119894thUE119887IV)

119879

(12)

by taking the conjugate of the second and the fourth elementsof R

119901sim119894thUE119887

The final output is obtained by the functionalblock of equal gain combining (EGC) as

X

=

3

sum

119887=1

(119901sim119894thUE

119887I

119901sim119894thUE119887II

119901sim119894thUE119887III

119901sim119894thUE119887IV)

119879

(13)

Figure 5 describes the architecture ofmultiplexing systemby polarized 3D beams where each generated beam isdedicated to a piece of UE In this case the data rate is threetimes higher than the 3D-BF diversity system Here we alsoconsider multiple users with each of them equipping threecolocated antenna branches and note that in these two pro-posed schemes the zero-forcing BF is assumed and appliedat transmitter Tx (ie the BS) Compared with diversity casethe proposedmultiplexing scheme is relatively simple that thereceived signal for a specific UE after EGC process can begiven as

R119901sim119894thUE

119887

=

3

sum

119887=1

(h119901sim119894thUE

119887

(WTx119901sim119894thUE

119887

⊙ S119901sim119894thUE

119887

) + n119901sim119894thUE

119887

)

(14)

32 Array Selection Scheme for PM-MIMOArray System Thesharp beam as illustrated in Figure 2(b) performs quite wellin terms of BF interferences mitigation However it is notefficient to assign all AEs of a MUX to form one beamespecially for cell-edge UEs Overall AEs in a MUX can bedivided into several groups to form beams for separate UEsand this part analyses the minimum number of AEs requiredto mitigate BF interferences

Let us have two simultaneous beams point two adjacentpieces of UEs as demonstrated in Figure 6 where 119871 gives thebeam coverage and 119863 and 119889 denote the distance from UE toBS and the distance between the adjacent UEs respectivelyTo make the analysis meaningful we assume that there is asufficient amount of UE deployed in a cell and therewith theUEs are close each other resulting in 119889

1asymp V

1and 119889

2asymp V

2

According to Figure 6 in the case of UE (UE-1 and UE-2)located at a 3 dB beam area that is a half power beam-width(HPBW) area the HPBW needs to be controlled at less than2119889

1to avoid BF interferences On the other hand when UEs

(UE-3 and UE-4) are located at a beam peak area the HPBWcan be set larger than 2119889

2 In addition to assuming that UE is

distributed in a square cell which can be treated as a city blockfor horizontal BF or a building for vertical BF we provideFigure 7 for calculating average 119863 and 119889 Suppose that UEsfollow a spatial Poisson process with an intensity of 120588 so thenumber of UEs in a cell is given as

119870 = 1205881198712

(15)

The average distance between the BS and UE is calculated by

119863 = ∬1198712

1

1198712

119903 119889119903 119889120579

=2

1198712

(int

120603

0

int

119886 cos 120579

0

1199032

119889119903 119889120579 + int

1205872

120603

int

2119886 sin 120579

0

1199032

119889119903 119889120579)

=120585119871

2

(16)

where 120585 = ln(2 + radic5)12 + radic5 minus 2 ln((radic5 minus 1)2)3 asymp 1187The average distance between two adjacent pieces of UEs isgiven as

119889 = ∬119860

1

119860119903119889119903 119889120579 = int

2120587

0

int

119903UE

0

1199032

1205871199032

UE119889119903 119889120579 =

2

3119903UE (17)

where 119860 denotes the local coverage area of UE with a radiusof 119903UE depending on 120588

Because 119863 is calculated close to 1198712 the HPBW lt 2119889

needs to be maintained to avoid BF interferences Accordingto Su and Chang [16] we have

HPBW asymp 2

1003816100381610038161003816100381610038161003816arcsin(1391

120576

120587119875+ sin 120579

0)

1003816100381610038161003816100381610038161003816lt

4

3119903UE (18)

where 120576 denotes the array spacing factor that is 120576 = 120582119904 with119904 and 120582 representing the array spacing and signal wavelengthrespectively 120579

0is the signal incidence angle shifted from

the bore-sight direction and the antenna bore-sight is theaxis vertical to the orientation of the array alignment Forexample if the radius of a userrsquos local area (119903UE) is 15meters atleast 8 AEs are required to avoid BF interferences when 120576 = 2

and 1205790= 1205874 Please note that the above analysis is derived

based on the isotropic array antenna system The requirednumber of AEs may decrease by using the dipole antennabecause it does not radiate in the longitudinal direction ofan antenna structure that maintains a higher radiation gaincompared with the isotropic antenna

As discussed in Su andChang [16] and Liu [22] the beam-width is increased significantly when the beam steers to anangle far off the bore-sight direction such as the case of 120579

0in

(18) reaching 90∘ In order to avoid beam-with extension wepropose a scheme to cope with the large off bore-sight angleby dynamically selecting the set of polarized branches for 3D-BF that can effectivelyworkwithout increasing the dimensionof the array system As depicted in Figure 8 let 120572

119896 120573

119896 and 120574

119896

denote the acute angles corresponding to the119883119884 and119885 axesof the 119896th incident signal we have

120572119896= arcsin

radic1198872

119896

+ 1198882

119896

119863119896

120573119896= arcsin

radic1198862

119896

+ 1198882

119896

119863119896

120574119896= arcsin

radic1198862

119896

+ 1198872

119896

119863119896

(19)

Mobile Information Systems 7

11Tx

w

21Tx

w

31Tx

w

12

Txw

22Tx

w

32

Txw

Yextension

X

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

B1

B2

B3

B1

B2

B3

B1

B2

B3

13

Txw

23Tx

w

33

Txw

A1B2A1B3

A2B3

A3B3

A1B1

A2B2

A2B1

A3B2

A3B1

Kth UE

GI removal and FFTqth MUX of

PM-MIMO

APminus2B3

APminus2B2

APminus2B1

APminus1B2

APminus1B1

APminus1B3

APB3

APB2

APB1

wTxP2

wTxP3

wTxP1

wTx(pminus2)2

wTx(pminus2)3

wTx(pminus2)1

wTx(pminus1)3

wTx(pminus1)2

wTx(pminus1)1

B3

B2

B1

B3

B2

B1

B3

B2

B1

1st UE

2nd UE

3rd UE

(K minus 1)th UE

(K minus 2)th UE

IFFT and GI

Figure 5 Multiplexing system architecture by polarized 3D beams

BS

HPBW

UE-3

UE-4UE-2

UE-1

1

2

L

d1

d2D4

D3

D1

D2

Figure 6 Two beams steer toward two adjacent pieces of UE

8 Mobile Information Systems

UE-2

UE-1D

L

dr

r

UE

120579

minusL2

L2

PM-MIMO

Vertical BF plane

Horizontal BF

120603plane

X

Y

Z

0

Figure 7 Illustration of a square cell used for calculating 119863 and 119889

x

z

y

ck

bk

ak

Dk

120574k

120573k120572k

kth incident signal

PM-MIMO

Figure 8 Selection on the set of branches for 3D-BF via incident signal

where 120572119896 120573

119896 and 120574

119896isin (0 1205872) In order to avoid beam-

width extension by considering the off bore-sight anglethe following criteria need to be carried out for 3D-BFapplications

(i) When 120572119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198613to form the beam for the 119896th incident signal

(ii) When 120573119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198612to form the beam for the 119896th incident signal

(iii) When 120574119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198611to form the beam for the 119896th incident signal

Let 1199101(119905) 119910

2(119905) 119910

119896(119905) denote the incident signal

sequences that come from random directions Figure 9 thenprovides the flowchart of the proposed AE selection schemefor the PM-MIMO system According to Figure 9 the pro-posed scheme at first detects the incident signal sequencesand determines the minimum number of AEs used for 3D-BF via the criterion provided by (18) And then the proposedscheme categorizes the incident signal sequences into threecategories according tomax(120572

119896 120573

119896 120574

119896) For each category the

proposed schemes prepare the set of branches used for 3D-BF via the criteria provided before If the 3D-BF application

is dedicated to the cell-edge users the diversity by usingpolarized 3D beams is employed to maintain the cell-edgeusersrsquo performances Otherwise multiplexing via polarized3D beams is suggested in order to increase overall systemthroughput

4 Blind Channel Estimation to Avoid PilotContamination in PM-MIMO Array System

Theoretically the M-MIMO system is proved to have manyattractive features in wireless communications Howeverthese features are obtained mainly based on the perfectchannel estimation Practically the BS does not have perfectchannel state information that limits the exploration of M-MIMO systems Moreover conventional channel estimationby using training sequences may not be applicable to M-MIMO systems because usually there are tens or hundreds ofantennae applied in M-MIMO systems Spectrum efficiencycould not only be decreased dramatically by reserving manypilots for channel estimation but pilot contamination alsolimits performance because the pilot positions in a resourceblock have to be reused due to massive antenna employment[23ndash26]

Mobile Information Systems 9

No No

No

Start

Detection of incident signalfrom K UEs y1(t) y2(t) yK(t)

For yk(t) find max(120572k 120573k 120574k)

If 120572k is maximum If 120573k is maximum

YesYes

If yA119901B119887k

(t) belongs to cell-edge UE

Select AEs for yA119901B119887k

(t) and explore

diversity gain by STBC with 3D-BF

Select AEs for yA119901B119887k

(t) and explore

multiplexing gain by 3D-BF

k = k + 1

If k gt K

If k gt K

Yes

End

No

Categorize yk(t) to yA119901B3k

(t) max(120572k 120573k 120574k) = 120572k

Categorize yk(t) to yA119901B1k

(t) max(120572k 120573k 120574k) = 120574k

Categorize yk(t) to yA119901B2k

(t) max(120572k 120573k 120574k) = 120573k

Yes

Yes

No

Figure 9 Flowchart of the proposed AE selection scheme for PM-MIMO system

The BCE approach which requires no or a minimalnumber of pilots needs to be applied in M-MIMO systemsOne of the BCE strategies is based on eigenvalue decompo-sition (EVD) for the covariance matrix of a received signalthat needs to preserve pairwise orthogonality among channelvectors [27ndash29] Let us define an M-MIMO system model as

y119896= Hx

119896+ n

119896 (20)

where x119896is the transmitted symbolsH is an119872-by-119873 channel

matrix between the BS and the 119896th UE and n119896denotes

the additive white noise The covariance matrix of thereceived signal is then defined by

Ry119896

≜ y119896y119867119896

= HRx119896

H119867

+ Rn119896

(21)

where 119867 represents the Hermitian Transpose operationAdditionally multiplyingH at both sides of (21) we have

Ry119896

H = HRx119896

H119867H +H (22)

10 Mobile Information Systems

From the law of large number the channel vectors betweenthe BS and the deployed UEs become very long random andpairwise orthogonal which satisfies the condition

1

119872H119867H 997888rarr I

119873 as 119872 997888rarr infin (23)

Thereafter the estimated channel can be obtained as theeigenvectors of Ry

119896

via EVD processing [29]Note that since we focus on the link-level performance

the element of channel matrix H should be normalized andonly the additive noise and fast fading effects are taken intoconsideration to generate H If the array spacing is largerthan a half wave-length the elements of H would be lowlycorrelated and then the condition of (23) is easy to be satisfiedas reported elsewhere [30] where the BS AEs are usually sep-arated by several wave-lengths resulting in an uncorrelatedTx radiation pattern to preserve the pairwise orthogonalityamong channel vectors However in space-limitedM-MIMOsystems the pairwise orthogonality cannot be maintainedbecause the adjacent AE space is fixed normally at equal

or less than a half signal wave-length Consequently in thispaper we modify the EVD-based blind channel estimationscheme studied in Ngo and Larsson [29] The modifiedBCE approach can exploit the pairwise orthogonality via theparticular characteristics of PM-MIMO systems that is thepolarized cross-branch links in the system usually are uncor-related even though the adjacent AE spacing is set equal toor less than a half signal wave-length [17]

Based on other researches [14 16 31] an extension of thechannel matrix for PM-MIMO systems can be represented as

HPM-MIMO (119905)

= (

hTx1198601minusRx119860

1(119905) sdot sdot sdot hTx119860

1minusRx119860

(119905)

d

hTx119860119875minusRx119860

1(119905) sdot sdot sdot hTx119860

119875minusRx119860

(119905)

)

(24)

where

hTx119860119901minusRx119860

(119905) = radic

120578

119868

119868

sum

119894=1

(

ℎTx1198601199011198611minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198611(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198612(119905) ℎTx119860

1199011198612minusRx119860

1198612(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198612(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198613(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198613(119905) ℎTx119860

1199011198613minusRx119860

1198613(119905)

) (25)

Here 120578 and 119868 denote the transmit power and the numberof scatterers respectively Channel matrix (24) has a size of3119875-by-3 which is composed of 3-by-3 submatrices Eachsubmatrix holds the polarized cross-branch links between the119875th AE of Tx (the BS) and the th AE (UE) of receiver (Rx)Please note that throughout the paper theUE is assumedwithone AE that is = 1 The channel vectors of submatrix(25) are random and pairwise orthogonal because the polar-ized links from a Tx AE with three orthogonal branches toa single Rx branch are usually highly orthogonal [17] Con-sequently we can apply the EVD-based BCE via submatrixof (25) By redefining the covariance matrix of the receivedsignal as

Ry119896

≜ y119896y119867119896

= hTx119860119901minusRx119860

Rx119896

h119867Tx119860119901minusRx119860

+ Rn119896

(26)

the estimated channel can be obtained as the eigenvec-tors of Ry

119896

via EVD processing because the condition of(13)h119867Tx119860

119901minusRx119860

hTx119860119901minusRx119860

rarr I3is satisfied

5 Performance Verification

Table 1 lists the parameters settings of the performance veri-fication based on the LTE-A specification [32] The downlinkdata mapping for LTE-A resource blocks used in simulationsis demonstrated in Figure 10 which is based on theQO-STBC

symbol matrix of (5)We use the training sequences providedby [32] which are defined as

119903119897119899119904(119898) =

1

radic2(1 minus 2 sdot 119888 (2119898))

+ 1198951

radic2(1 minus 2 sdot 119888 (2119898 + 1))

(27)

where 119898 = 0 1 2119873max119863119871

119877119861

minus 1 The pilot density is 143and the initialization of 119888 is defined as

119888init = 210

sdot (7 sdot (119899119904+ 1) + 119897 + 1) sdot (2 sdot 119873

cellID + 1) + 2

sdot 119873cellID + 119873CP

(28)

where 119899119904is the slot number within a frame and

119873CP =

1 for normal CP

0 for extended CP(29)

Figure 11 depicts the probability densities of the HPBWgenerated in simulations where the HPBW can be effectivelykept as 50∘ on average by using the proposed AE selectionscheme of Figure 9 However the average HPBW extends byabout 15∘ when not considering the off bore-sight angle effectThis demonstrates that the proposed AE selection scheme isrobust that can optimize the generated beamwidth to avoidBF interference

Mobile Information Systems 11

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Branch A1B1 Branch A2B1

(a) Data mapping at Tx1198601199011198611

minus

minus

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PA1B2

PA1B2

PA1B2

PA1B2

1110

PA2B2

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PA2B2

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Figure 10 Downlink data mapping of the LTE-A resource blocks used in the simulation

12 Mobile Information Systems

90

0005

001

0015

002

0025

003

With the proposed AE selection schemeWithout the proposed AE selection scheme

30 40 50 60 70 800

HPBW (deg)

Figure 11 Probability density of HPBW

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300

Case 2 PACE outdoor LOS 3kmhCase 3 PACE outdoor LOS 3kmh

Case 1 PACE outdoor LOS 3kmhCase 3 PACE outdoor NLOS 3kmhCase 2 PACE outdoor NLOS 3kmhCase 1 PACE outdoor NLOS 3kmh

EbN0 (dB)

Figure 12Users average BLERperformances based on the proposeddiversity system architecture

Figure 12 compares the usersrsquo average block error rate(BLER) performances obtained based on the proposeddiversity system architecture by using different transmissionschemes including Case 1 without STBC and TxBF Case2 with STBC only and Case 3 with STBC and TxBF viathe LTE pilot-assistant practical channel estimation (PACE)approach According to Figure 12 Case 1 has the worstperformance because there is no space-time coding and BFgain achieved About 17 dB of signal-to-noise ratio (SNR)gain at the target BLER can be achieved by Case 2 comparedwith Case 1 under the non-line-of-sight NLOS scenarioThere is about a 1 dB SNR gain that can be further achievedby employing the TxBF of Case 3 In addition the simulationresults under the LOS scenario are also provided as acomparison where almost 7 dB gain can be obtained whenthe LOS exists for those three cases

Next we simulate the BCE approaches and compare itsefficiency with the PACE based on the proposed diversitysystemarchitecture Figure 13 demonstrates the usersrsquo averageBLER via PACE and BCE approaches for three different

Table 1 Simulation parameters

Parameters ValueCarrier frequency 18GHzSystem bandwidth 20MHzFFT size 2048Number of data carriers 1200Number of samples in CP 144Subcarrier spacing 15 kHzBS antenna configuration(PM-MIMO) 1 MUX times 32 AE times 3 branches

BS AE spacing Half wavelengthUserrsquos antenna configuration 1 AE times 3 branches

Number of users 4 for 3D-BF diversity12 for 3D-BF multiplexing

Radius of userrsquos local area (119903UE) 15mAntenna type DipoleModulation QPSK

Number of scatterersOutdoor 4 clusters with 16scatterers per cluster (64 in

total)Scattering sphere radius 10mVelocity of UEs 3 60 and 120 kmhFading Flat

XPD value 58 dB and 97 dB for NLOSand LOS

Correlation 032 and 034 for NLOS andLOS

Rician 119870-factor 9 dB

userrsquos velocities including 3 60 and 120 kmh under theNLOS scenario An extension of other researches [14 31] isapplied to simulations of the polarized MIMO channel forwhich channel characteristics are also listed in Table 1 Wesee that the PACE performance decreases a lot due to highmobility at 60 and 120 kmh which indicates that the numberof pilots is not enough to compensate the channel correctlyin an environment with fast time-varying phase responseThe pilot density is 143 for PACE scheme and by consid-ering the trade-off regarding spectrum efficiency BCE thatrequires no or a minimal number of pilots might be betteremployed Figure 13 additionally shows the performances ofBCE schemes where performance is found that is not relevantto the userrsquos velocity Compared with the BCE reported byNgo and Larsson [29] our proposed BCE performance isbetter because the EVD is based on low correlated submatrixand has less complexity for doing the EVD based on asubmatrix with a smaller size Due to no pilot contaminationby BCE approach the proposed BCE outperforms PACEfor a velocity of 3 kmh when 119864

119887119873

0is less than 25 dB

However BCE has a higher complexity than PACE and itis condition constraint Again according to Figure 13 BCEperforms worse than PACE with a velocity of 3 kmh when119864119887119873

0is larger than 25 dB and the trend of error floor for

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

10minus1

100

UEs

aver

age B

LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia

International Journal of

Biomedical Imaging

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

Advances in

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RoboticsJournal of

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

2 Mobile Information Systems

can be realized by the proposed PM-MIMO system and thegenerated beams can be steered and varied at119883-119884119883-119885 and119884-119885 planes respectivelyThe system architectures of diversityand multiplexing schemes achieved by polarized 3D beamsare provided based on the proposed PM-MIMOarray systemA robust array selection scheme for 3D-BF applications isadditionally proposed to efficiently optimize the beam-widthand to enhance system performance by the exploration ofdiversity and multiplexing gains

Normally in M-MIMO systems when the number of BSantennae grows large the size of M-MIMO channel matrixgrows largeThe vector ofM-MIMO channelmatrix becomesvery long and any two of them are pairwise orthogonalHowever in a space-limited system pairwise orthogonalitycannot be maintained because the adjacent AE space isusually set equal to or to less than a half signal wave-length Therefore for this paper we additionally modifieda conventional blind channel estimation (BCE) approach toexploit the pairwise orthogonality according to the particularcharacteristics of PM-MIMO systems That is the polarizedcross-branch links in the system are usually uncorrelated [17]The proposed BCE approach is presented for PM-MIMO toavoid the pilot contamination and to enhance the systemspectrum efficiency By applying our proposals under thepolarized MIMO channel model Monte Carlo simulationsfinally confirm the validity of our proposals

The remaining parts of this paper are organized asfollows Section 2 describes the proposed PM-MIMO arraysystem and the proposed AE selection scheme is providedin Section 3 In Section 4 a BCE approach for PM-MIMO isintroduced and the simulation results are demonstrated anddiscussed in Section 5 Finally our conclusions are drawn inSection 6

2 PM-MIMO Array System

Figure 1 provides an example of a uniform linear array (ULA)with antenna polarization in the array and branch (AampB)multiple antennae configuration where three orthogonallycolocated antenna branches are fixed at each AE (ie antennaport) The beam-width is proved to be relevant to array con-figuration where it is inversely proportional to the numberof AEs and array element spacing Because the spacing ofthree colocated branches at each AE is set to zero as shownin Figure 1 which makes beam-width scale up to 360∘ thebeams should be generated via corresponding cross-arraybranches rather than the colocated branches at each AE [16]Therefore we can obtain three orthogonal beams generatedby a polarized ULA as follows

(i) Beam steered in 119883-119884 plane is generated by thebranches set of 119860

1199011198611 where 119901 is the index of AE

(ii) Beam steered in 119883-119885 plane is generated by thebranches set of 119860

1199011198612

(iii) Beam steered in 119884-119885 plane is generated by thebranches set of 119860

1199011198613

Let 1198751198611

(120579 120601 12057901

) 1198751198612

(120579 120601 12057902

) and 1198751198613

(120579 120601 12057903

)

represent the beam radiation patterns generated by the

Z

XY

A1B1 A2B1

A2B3A1B3

A1B2 A2B2

middot middot middot middot middot middot

ApB2

ApB3

ApB1

Array elementAntenna branch

Figure 1 Uniform linear array with antenna polarization

above three sets 1198601199011198611 119860

1199011198612 and 119860

1199011198613 respectively We

have

1198751198611

(120579 120601 12057901

) =

119873

sum

119899=1

119890119895(119899minus1)(2120587120576)(sin 120579minussin 120579

01)

=sin ((120587119873120576) (sin 120579 minus sin 120579

01))

119873 sdot sin ((120587120576) (sin 120579 minus sin 12057901

))

(1)

1198751198612

(120579 120601 12057902

) =

119873

sum

119899=1

119890119895(119899minus1)(2120587120576)(sin 120601minussin 120579

02)

=sin ((120587119873120576) (sin120601 minus sin 120579

02))

119873 sdot sin ((120587120576) (sin120601 minus sin 12057902

))

(2)

1198751198613

(120579 120601 12057903

) =

119873

sum

119899=1

119890119895(119899minus1)(2120587120576)(sin(1205872minus120601)minussin 120579

03)

=sin ((120587119873120576) (cos120601 minus sin 120579

03))

119873 sdot sin ((120587120576) (cos120601 minus sin 12057903

))

(3)

where 120579 and 120601 denote the azimuth and elevation angle ofthe radiation pattern 120576 is the array element spacing factordefined by [16] and 120579

01 120579

02 and 120579

03are the off bore-sight

angles corresponding to1198601199011198611119860

1199011198612 and119860

1199011198613 respectively

[16] Figure 2(a) with 119873 = 8 then depicts the 3D beamsgenerated by a triple polarized ULA (TPULA) system via (1)(2) and (3) where three orthogonal beams can be steered andvaried separately on the 119883-119884 119885-119883 and 119884-119885 planes For thesecond subfigure of Figure 2(a) 120579

01 120579

02 and 120579

03are set as

30∘ According to Figure 2(b) a very narrow beam-width isobtained by applying a large number ofAEs for example119873 =

64 AEs that performs quite well in terms of BF interferencesmitigation

By employing the TPULA at each multiplexer (MUX)the structure of our proposed PM-MIMO array systemis illustrated in Figure 3 with the received signal being givenas

119910 =

119876

sum

119902=1

3

sum

119887=1

(119908119901119887119902

ℎ119901119887119902

119909119901119887119902

+ 119899119901119887119902

) (4)

where ℎ119901119887119902

is the subpolarized channel corresponding to119876th 119860

119901119861119887array element 119908

119901119887119902denotes the 3D-BF weights

multiplied at each antenna branch and 119901 (1 2 119875) 119887

(1 2 3) and 119902 (1 2 119876) represent the AE index branch

Mobile Information Systems 3

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus1

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus11

050

minus05minus1 1

050minus05

minus1

minus1 minus05 0 051 minus1minus050051

XX

ZZ

YY

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus11

Z

(a) 3D beams generated by a triple-polarized ULA system

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus1

1080604020minus02minus04minus06minus08minus11080604020minus02minus04minus06minus08minus11

08

06

04

02

0

minus02

minus04

minus06

minus08

minus1

X X

YY

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus1

Y

BW8 BW64

(b) Beam-width varied with different number of AEs being employed for example 8 and 64 AEs

Figure 2 3D beams generated by a polarized ULA

index andMUX index respectivelyThe 3D-BF which can beapplied for multipath reception or combination of relay sig-nals [18] is introduced as a promising technique inM-MIMOsystems to enhance the cellular performance by deployingantenna elements in both horizontal and vertical (HampV)dimensions [19] However different from the conventional3D-BF achieved by planar M-MIMO system to control thedowntilted beam in a vertical domain the proposed PM-MIMO realizes the 3D-BF via the linear combination ofpolarized beams It highlights the fact that the 3D-BF not onlyis addressed by theHampV exploration but also can be achievedby antenna polarizationmeanwhile the antenna polarizationalso serves as a pivotal solution dedicated to space constraintin M-MIMO systems

3 Diversity and MultiplexingAchieved by Polarized 3D Beams withan Array Selection Scheme

31 System Architecture Figure 4 describes the architectureof the proposed diversity system via polarized 3D beamswhere the multiple users with each equipping three colocatedantenna branches are considered As studied by Dao et al[17] the cross-array links (eg from BS 119860

11198611and 119860

21198611

to UE 1198611) can be highly correlated by setting the AE

space equal to or less than a half-wavelength The cross-branch links (eg from BS 119860

11198611and 119860

11198612to UE 119861

1) on

the other hand are usually uncorrelated due to the spacepolarizationThis inspired us to incorporate space-time block

4 Mobile Information Systems

MUX-Q

A1B2

A1B1

A1B3

A2B2

A2B3A2B1

APB2

APB1

APB3

MUX-1MUX-2

sQ(t)

X

Y

w12q(t)

w13q(t)

w11q(t)

w22q(t)

w23q(t)

w21q(t)

wP2q(t)

wP3q(t)

wP1q(t)

s2(t)s1(t) S(t)

Figure 3 Structure of the proposed PM-MIMO array system

coding (STBC) and BF techniques simultaneously in theTPULA system to boost performance Moreover in orderto achieve full-rate coding with an odd number of transmitantennae quasi-orthogonal STBC (QO-STBC) has emergedin the literature [20 21] which fully explores diversity gainbut increases the complexity of decoding due to nonorthog-onal interference In this paper the proposed diversityscheme combines QO-STBC for three transmit antennaeand BF techniques via the TPULA system as illustrated inFigure 4

In Figure 4 the BF weights (119908Tx119901119887

) are multiplied beforethe inverse fast Fourier transform (IFFT) block of the BSX

119901in (5) is the transmitted QO-STBC symbol matrix [20]

X119901= (

119909II 119909III 119909IV

119909lowast

I minus119909lowast

IV 119909lowast

III

119909IV 119909I 119909II

119909lowast

III minus119909lowast

II 119909lowast

I

)

119868-by-119869

(5)

where the Roman numeral is the symbol index 119894 is the timeindexmodulo of 4 (119868 = 4) and 119895 is the antenna indexmoduloof 3 (119869 = 3) At each UE the QO-STBC decoding is appliedafter the FFT block at each antenna branch [20] and then we

can have the received signal for each branch of a specific UEbefore QO-STBC decoding as

R119901sim119894thUE

119887

= (h119901sim119894thUE

119887

(WTx119901sim119894thUE

119887

⊙ X119901sim119894thUE

119887

)119879

)

119879

+ n119901sim119894thUE

119887

= (WTx119901sim119894thUE

119887

⊙ X119901sim119894thUE

119887

) h119879119901sim119894thUE

119887

+ n119901sim119894thUE

119887

= (119903119901sim119894thUE

119887I 119903

119901sim119894thUE119887II 119903

119901sim119894thUE119887III 119903

119901sim119894thUE119887IV)

119879

(6)

where ldquo⊙rdquo denotes the Hadamard product and WTx119901

is theTxBF weighting matrix given by

WTx119901sim119894thUE

119887

= (

119908Tx1199011

119908Tx1199012

119908Tx1199013

119908Tx1199011

119908Tx1199012

119908Tx1199013

119908Tx1199011

119908Tx1199012

119908Tx1199013

119908Tx1199011

119908Tx1199012

119908Tx1199013

) (7)

h119901sim119894thUE

119887

is the vector of the polarized cross-branch linksgiven by

h119901sim119894thUE

119887

= (ℎ1199011sim119894thUE

119887

ℎ1199012sim119894thUE

119887

ℎ1199013sim119894thUE

119887) (8)

Mobile Information Systems 5

QO-STBCdecoding

QO-STBCdecoding

QO-STBCdecoding

IFFT and GI extension

GI removal

1st UE

A1B2

A1B1

A1B3

A2B2A2B3

A2B1

A3B2A3B3

A3B1

and FFT

B1

B2

Y

X

qth MUX ofPM-MIMO

APminus2B3

APminus2B2

APminus2B1

APminus1B2

APminus1B1

APminus1B3

APB3

APB2

APB1

wTx12

wTx13

wTx11

wTx22

wTx23

wTx21

wTx32

wTx33

wTx31

wTxP2

wTxP3

wTxP1

wTx(pminus2)2

wTx(pminus2)3

wTx(pminus2)1

wTx(pminus1)2

wTx(pminus1)3

wTx(pminus1)1

B3

B3

B2

B1

Kth UE

EGC

EGC

QO-STBC

QO-STBC

QO-STBCdecoding

QO-STBCdecoding

QO-STBCdecoding

Figure 4 Diversity system architecture by polarized 3D beams

and n119901sim119894thUE

119887

is the noise vector given by

n119901sim119894thUE

119887

= (120590119901sim119894thUE

119887I 120590

119901sim119894thUE119887II 120590

119901sim119894thUE119887III 120590

119901sim119894thUE119887IV)

119879

(9)

The STBC decoding applied thereafter gives

X119901sim119894thUE

119887

= D119901sim119894thUE

119887

Τ119901sim119894thUE

119887

= (119901sim119894thUE

119887I

119901sim119894thUE119887II

119901sim119894thUE119887III

119901sim119894thUE119887IV)

119879

(10)

Here D119901sim119902119887

is the STBC decoding matrix which is modifiedbased on equation (12) in [20] by considering TxBF weights

D119901sim119894thUE

119887

=

((((

(

0 119908Tx1199011

ℎ1199011sim119894thUE

119887

(119908Tx1199012

)lowast

ℎlowast

1199012sim119894thUE

119887

119908Tx1199013

ℎ1199013sim119894thUE

119887

(119908Tx1199011

)lowast

ℎlowast

1199011sim119894thUE

119887

0 (119908Tx1199013

)lowast

ℎlowast

1199013sim119894thUE

119887

minus119908Tx1199012

ℎ1199012sim119894thUE

119887

(119908Tx1199012

)lowast

ℎlowast

1199012sim119894thUE

119887

119908Tx1199013

ℎ1199013sim119894thUE

119887

0 119908Tx1199011

ℎ1199011sim119894thUE

119887

(119908Tx1199013

)lowast

ℎlowast

1199013sim119894thUE

119887

minus119908Tx1199012

ℎ1199012sim119894thUE

119887

(119908Tx1199011

)lowast

ℎlowast

1199011sim119894thUE

119887

0

))))

)

(11)

6 Mobile Information Systems

where Τ119901sim119902119887

is defined as

Τ119901sim119894thUE

119887

= (119901sim119894thUE

119887I

lowast

119901sim119894thUE119887II

119901sim119894thUE119887III

lowast

119901sim119894thUE119887IV)

119879

(12)

by taking the conjugate of the second and the fourth elementsof R

119901sim119894thUE119887

The final output is obtained by the functionalblock of equal gain combining (EGC) as

X

=

3

sum

119887=1

(119901sim119894thUE

119887I

119901sim119894thUE119887II

119901sim119894thUE119887III

119901sim119894thUE119887IV)

119879

(13)

Figure 5 describes the architecture ofmultiplexing systemby polarized 3D beams where each generated beam isdedicated to a piece of UE In this case the data rate is threetimes higher than the 3D-BF diversity system Here we alsoconsider multiple users with each of them equipping threecolocated antenna branches and note that in these two pro-posed schemes the zero-forcing BF is assumed and appliedat transmitter Tx (ie the BS) Compared with diversity casethe proposedmultiplexing scheme is relatively simple that thereceived signal for a specific UE after EGC process can begiven as

R119901sim119894thUE

119887

=

3

sum

119887=1

(h119901sim119894thUE

119887

(WTx119901sim119894thUE

119887

⊙ S119901sim119894thUE

119887

) + n119901sim119894thUE

119887

)

(14)

32 Array Selection Scheme for PM-MIMOArray System Thesharp beam as illustrated in Figure 2(b) performs quite wellin terms of BF interferences mitigation However it is notefficient to assign all AEs of a MUX to form one beamespecially for cell-edge UEs Overall AEs in a MUX can bedivided into several groups to form beams for separate UEsand this part analyses the minimum number of AEs requiredto mitigate BF interferences

Let us have two simultaneous beams point two adjacentpieces of UEs as demonstrated in Figure 6 where 119871 gives thebeam coverage and 119863 and 119889 denote the distance from UE toBS and the distance between the adjacent UEs respectivelyTo make the analysis meaningful we assume that there is asufficient amount of UE deployed in a cell and therewith theUEs are close each other resulting in 119889

1asymp V

1and 119889

2asymp V

2

According to Figure 6 in the case of UE (UE-1 and UE-2)located at a 3 dB beam area that is a half power beam-width(HPBW) area the HPBW needs to be controlled at less than2119889

1to avoid BF interferences On the other hand when UEs

(UE-3 and UE-4) are located at a beam peak area the HPBWcan be set larger than 2119889

2 In addition to assuming that UE is

distributed in a square cell which can be treated as a city blockfor horizontal BF or a building for vertical BF we provideFigure 7 for calculating average 119863 and 119889 Suppose that UEsfollow a spatial Poisson process with an intensity of 120588 so thenumber of UEs in a cell is given as

119870 = 1205881198712

(15)

The average distance between the BS and UE is calculated by

119863 = ∬1198712

1

1198712

119903 119889119903 119889120579

=2

1198712

(int

120603

0

int

119886 cos 120579

0

1199032

119889119903 119889120579 + int

1205872

120603

int

2119886 sin 120579

0

1199032

119889119903 119889120579)

=120585119871

2

(16)

where 120585 = ln(2 + radic5)12 + radic5 minus 2 ln((radic5 minus 1)2)3 asymp 1187The average distance between two adjacent pieces of UEs isgiven as

119889 = ∬119860

1

119860119903119889119903 119889120579 = int

2120587

0

int

119903UE

0

1199032

1205871199032

UE119889119903 119889120579 =

2

3119903UE (17)

where 119860 denotes the local coverage area of UE with a radiusof 119903UE depending on 120588

Because 119863 is calculated close to 1198712 the HPBW lt 2119889

needs to be maintained to avoid BF interferences Accordingto Su and Chang [16] we have

HPBW asymp 2

1003816100381610038161003816100381610038161003816arcsin(1391

120576

120587119875+ sin 120579

0)

1003816100381610038161003816100381610038161003816lt

4

3119903UE (18)

where 120576 denotes the array spacing factor that is 120576 = 120582119904 with119904 and 120582 representing the array spacing and signal wavelengthrespectively 120579

0is the signal incidence angle shifted from

the bore-sight direction and the antenna bore-sight is theaxis vertical to the orientation of the array alignment Forexample if the radius of a userrsquos local area (119903UE) is 15meters atleast 8 AEs are required to avoid BF interferences when 120576 = 2

and 1205790= 1205874 Please note that the above analysis is derived

based on the isotropic array antenna system The requirednumber of AEs may decrease by using the dipole antennabecause it does not radiate in the longitudinal direction ofan antenna structure that maintains a higher radiation gaincompared with the isotropic antenna

As discussed in Su andChang [16] and Liu [22] the beam-width is increased significantly when the beam steers to anangle far off the bore-sight direction such as the case of 120579

0in

(18) reaching 90∘ In order to avoid beam-with extension wepropose a scheme to cope with the large off bore-sight angleby dynamically selecting the set of polarized branches for 3D-BF that can effectivelyworkwithout increasing the dimensionof the array system As depicted in Figure 8 let 120572

119896 120573

119896 and 120574

119896

denote the acute angles corresponding to the119883119884 and119885 axesof the 119896th incident signal we have

120572119896= arcsin

radic1198872

119896

+ 1198882

119896

119863119896

120573119896= arcsin

radic1198862

119896

+ 1198882

119896

119863119896

120574119896= arcsin

radic1198862

119896

+ 1198872

119896

119863119896

(19)

Mobile Information Systems 7

11Tx

w

21Tx

w

31Tx

w

12

Txw

22Tx

w

32

Txw

Yextension

X

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

B1

B2

B3

B1

B2

B3

B1

B2

B3

13

Txw

23Tx

w

33

Txw

A1B2A1B3

A2B3

A3B3

A1B1

A2B2

A2B1

A3B2

A3B1

Kth UE

GI removal and FFTqth MUX of

PM-MIMO

APminus2B3

APminus2B2

APminus2B1

APminus1B2

APminus1B1

APminus1B3

APB3

APB2

APB1

wTxP2

wTxP3

wTxP1

wTx(pminus2)2

wTx(pminus2)3

wTx(pminus2)1

wTx(pminus1)3

wTx(pminus1)2

wTx(pminus1)1

B3

B2

B1

B3

B2

B1

B3

B2

B1

1st UE

2nd UE

3rd UE

(K minus 1)th UE

(K minus 2)th UE

IFFT and GI

Figure 5 Multiplexing system architecture by polarized 3D beams

BS

HPBW

UE-3

UE-4UE-2

UE-1

1

2

L

d1

d2D4

D3

D1

D2

Figure 6 Two beams steer toward two adjacent pieces of UE

8 Mobile Information Systems

UE-2

UE-1D

L

dr

r

UE

120579

minusL2

L2

PM-MIMO

Vertical BF plane

Horizontal BF

120603plane

X

Y

Z

0

Figure 7 Illustration of a square cell used for calculating 119863 and 119889

x

z

y

ck

bk

ak

Dk

120574k

120573k120572k

kth incident signal

PM-MIMO

Figure 8 Selection on the set of branches for 3D-BF via incident signal

where 120572119896 120573

119896 and 120574

119896isin (0 1205872) In order to avoid beam-

width extension by considering the off bore-sight anglethe following criteria need to be carried out for 3D-BFapplications

(i) When 120572119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198613to form the beam for the 119896th incident signal

(ii) When 120573119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198612to form the beam for the 119896th incident signal

(iii) When 120574119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198611to form the beam for the 119896th incident signal

Let 1199101(119905) 119910

2(119905) 119910

119896(119905) denote the incident signal

sequences that come from random directions Figure 9 thenprovides the flowchart of the proposed AE selection schemefor the PM-MIMO system According to Figure 9 the pro-posed scheme at first detects the incident signal sequencesand determines the minimum number of AEs used for 3D-BF via the criterion provided by (18) And then the proposedscheme categorizes the incident signal sequences into threecategories according tomax(120572

119896 120573

119896 120574

119896) For each category the

proposed schemes prepare the set of branches used for 3D-BF via the criteria provided before If the 3D-BF application

is dedicated to the cell-edge users the diversity by usingpolarized 3D beams is employed to maintain the cell-edgeusersrsquo performances Otherwise multiplexing via polarized3D beams is suggested in order to increase overall systemthroughput

4 Blind Channel Estimation to Avoid PilotContamination in PM-MIMO Array System

Theoretically the M-MIMO system is proved to have manyattractive features in wireless communications Howeverthese features are obtained mainly based on the perfectchannel estimation Practically the BS does not have perfectchannel state information that limits the exploration of M-MIMO systems Moreover conventional channel estimationby using training sequences may not be applicable to M-MIMO systems because usually there are tens or hundreds ofantennae applied in M-MIMO systems Spectrum efficiencycould not only be decreased dramatically by reserving manypilots for channel estimation but pilot contamination alsolimits performance because the pilot positions in a resourceblock have to be reused due to massive antenna employment[23ndash26]

Mobile Information Systems 9

No No

No

Start

Detection of incident signalfrom K UEs y1(t) y2(t) yK(t)

For yk(t) find max(120572k 120573k 120574k)

If 120572k is maximum If 120573k is maximum

YesYes

If yA119901B119887k

(t) belongs to cell-edge UE

Select AEs for yA119901B119887k

(t) and explore

diversity gain by STBC with 3D-BF

Select AEs for yA119901B119887k

(t) and explore

multiplexing gain by 3D-BF

k = k + 1

If k gt K

If k gt K

Yes

End

No

Categorize yk(t) to yA119901B3k

(t) max(120572k 120573k 120574k) = 120572k

Categorize yk(t) to yA119901B1k

(t) max(120572k 120573k 120574k) = 120574k

Categorize yk(t) to yA119901B2k

(t) max(120572k 120573k 120574k) = 120573k

Yes

Yes

No

Figure 9 Flowchart of the proposed AE selection scheme for PM-MIMO system

The BCE approach which requires no or a minimalnumber of pilots needs to be applied in M-MIMO systemsOne of the BCE strategies is based on eigenvalue decompo-sition (EVD) for the covariance matrix of a received signalthat needs to preserve pairwise orthogonality among channelvectors [27ndash29] Let us define an M-MIMO system model as

y119896= Hx

119896+ n

119896 (20)

where x119896is the transmitted symbolsH is an119872-by-119873 channel

matrix between the BS and the 119896th UE and n119896denotes

the additive white noise The covariance matrix of thereceived signal is then defined by

Ry119896

≜ y119896y119867119896

= HRx119896

H119867

+ Rn119896

(21)

where 119867 represents the Hermitian Transpose operationAdditionally multiplyingH at both sides of (21) we have

Ry119896

H = HRx119896

H119867H +H (22)

10 Mobile Information Systems

From the law of large number the channel vectors betweenthe BS and the deployed UEs become very long random andpairwise orthogonal which satisfies the condition

1

119872H119867H 997888rarr I

119873 as 119872 997888rarr infin (23)

Thereafter the estimated channel can be obtained as theeigenvectors of Ry

119896

via EVD processing [29]Note that since we focus on the link-level performance

the element of channel matrix H should be normalized andonly the additive noise and fast fading effects are taken intoconsideration to generate H If the array spacing is largerthan a half wave-length the elements of H would be lowlycorrelated and then the condition of (23) is easy to be satisfiedas reported elsewhere [30] where the BS AEs are usually sep-arated by several wave-lengths resulting in an uncorrelatedTx radiation pattern to preserve the pairwise orthogonalityamong channel vectors However in space-limitedM-MIMOsystems the pairwise orthogonality cannot be maintainedbecause the adjacent AE space is fixed normally at equal

or less than a half signal wave-length Consequently in thispaper we modify the EVD-based blind channel estimationscheme studied in Ngo and Larsson [29] The modifiedBCE approach can exploit the pairwise orthogonality via theparticular characteristics of PM-MIMO systems that is thepolarized cross-branch links in the system usually are uncor-related even though the adjacent AE spacing is set equal toor less than a half signal wave-length [17]

Based on other researches [14 16 31] an extension of thechannel matrix for PM-MIMO systems can be represented as

HPM-MIMO (119905)

= (

hTx1198601minusRx119860

1(119905) sdot sdot sdot hTx119860

1minusRx119860

(119905)

d

hTx119860119875minusRx119860

1(119905) sdot sdot sdot hTx119860

119875minusRx119860

(119905)

)

(24)

where

hTx119860119901minusRx119860

(119905) = radic

120578

119868

119868

sum

119894=1

(

ℎTx1198601199011198611minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198611(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198612(119905) ℎTx119860

1199011198612minusRx119860

1198612(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198612(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198613(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198613(119905) ℎTx119860

1199011198613minusRx119860

1198613(119905)

) (25)

Here 120578 and 119868 denote the transmit power and the numberof scatterers respectively Channel matrix (24) has a size of3119875-by-3 which is composed of 3-by-3 submatrices Eachsubmatrix holds the polarized cross-branch links between the119875th AE of Tx (the BS) and the th AE (UE) of receiver (Rx)Please note that throughout the paper theUE is assumedwithone AE that is = 1 The channel vectors of submatrix(25) are random and pairwise orthogonal because the polar-ized links from a Tx AE with three orthogonal branches toa single Rx branch are usually highly orthogonal [17] Con-sequently we can apply the EVD-based BCE via submatrixof (25) By redefining the covariance matrix of the receivedsignal as

Ry119896

≜ y119896y119867119896

= hTx119860119901minusRx119860

Rx119896

h119867Tx119860119901minusRx119860

+ Rn119896

(26)

the estimated channel can be obtained as the eigenvec-tors of Ry

119896

via EVD processing because the condition of(13)h119867Tx119860

119901minusRx119860

hTx119860119901minusRx119860

rarr I3is satisfied

5 Performance Verification

Table 1 lists the parameters settings of the performance veri-fication based on the LTE-A specification [32] The downlinkdata mapping for LTE-A resource blocks used in simulationsis demonstrated in Figure 10 which is based on theQO-STBC

symbol matrix of (5)We use the training sequences providedby [32] which are defined as

119903119897119899119904(119898) =

1

radic2(1 minus 2 sdot 119888 (2119898))

+ 1198951

radic2(1 minus 2 sdot 119888 (2119898 + 1))

(27)

where 119898 = 0 1 2119873max119863119871

119877119861

minus 1 The pilot density is 143and the initialization of 119888 is defined as

119888init = 210

sdot (7 sdot (119899119904+ 1) + 119897 + 1) sdot (2 sdot 119873

cellID + 1) + 2

sdot 119873cellID + 119873CP

(28)

where 119899119904is the slot number within a frame and

119873CP =

1 for normal CP

0 for extended CP(29)

Figure 11 depicts the probability densities of the HPBWgenerated in simulations where the HPBW can be effectivelykept as 50∘ on average by using the proposed AE selectionscheme of Figure 9 However the average HPBW extends byabout 15∘ when not considering the off bore-sight angle effectThis demonstrates that the proposed AE selection scheme isrobust that can optimize the generated beamwidth to avoidBF interference

Mobile Information Systems 11

PA2B1

PA2B1

PA2B1

PA2B1

0 1 3 4 5 6 7 8 9

0

1

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urce

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Branch A1B1 Branch A2B1

(a) Data mapping at Tx1198601199011198611

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

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PA1B2

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1110

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Reso

urce

blo

ck

01

98765432

xlowast4

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xlowast481110

20 1 3 4 5 6 7 8 9Subframe

131211131211 1020 1 3 4 5 6 7 8 9Subframe

10

x3

x7

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x27

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minus minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

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minus

minus

minus

minus

x97

x101

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x113

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Branch A1B2 Branch A2B2

(b) Data mapping at Tx1198601199011198612

xlowast49xlowast53

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urce

blo

ck

01

98765432

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PA1B3

PA1B3

PA1B3

PA1B3

1110

20 1 3 4 5 6 7 8 9Subframe

13121110

Branch A2B3

PA2B3PA2B3

PA2B3 PA2B3

x4

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Reso

urce

blo

ck

01

98765432

xlowast3

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xlowast471110

20 1 3 4 5 6 7 8 9Subframe

13121110

x4

x8

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x28

x32

x36

x40

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x48

x2

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x10

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x92

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x50

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x90

x94

x100x104

x108

x112

x116

x120

x124

x128

x132

x136

x140

x144

x98

x102

x106

x110

x114

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x122

x126

x130

x134

x138

x142

xlowast97

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xlowast135

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xlowast143

Branch A1B3

(c) Data mapping at Tx1198601199011198613

Figure 10 Downlink data mapping of the LTE-A resource blocks used in the simulation

12 Mobile Information Systems

90

0005

001

0015

002

0025

003

With the proposed AE selection schemeWithout the proposed AE selection scheme

30 40 50 60 70 800

HPBW (deg)

Figure 11 Probability density of HPBW

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300

Case 2 PACE outdoor LOS 3kmhCase 3 PACE outdoor LOS 3kmh

Case 1 PACE outdoor LOS 3kmhCase 3 PACE outdoor NLOS 3kmhCase 2 PACE outdoor NLOS 3kmhCase 1 PACE outdoor NLOS 3kmh

EbN0 (dB)

Figure 12Users average BLERperformances based on the proposeddiversity system architecture

Figure 12 compares the usersrsquo average block error rate(BLER) performances obtained based on the proposeddiversity system architecture by using different transmissionschemes including Case 1 without STBC and TxBF Case2 with STBC only and Case 3 with STBC and TxBF viathe LTE pilot-assistant practical channel estimation (PACE)approach According to Figure 12 Case 1 has the worstperformance because there is no space-time coding and BFgain achieved About 17 dB of signal-to-noise ratio (SNR)gain at the target BLER can be achieved by Case 2 comparedwith Case 1 under the non-line-of-sight NLOS scenarioThere is about a 1 dB SNR gain that can be further achievedby employing the TxBF of Case 3 In addition the simulationresults under the LOS scenario are also provided as acomparison where almost 7 dB gain can be obtained whenthe LOS exists for those three cases

Next we simulate the BCE approaches and compare itsefficiency with the PACE based on the proposed diversitysystemarchitecture Figure 13 demonstrates the usersrsquo averageBLER via PACE and BCE approaches for three different

Table 1 Simulation parameters

Parameters ValueCarrier frequency 18GHzSystem bandwidth 20MHzFFT size 2048Number of data carriers 1200Number of samples in CP 144Subcarrier spacing 15 kHzBS antenna configuration(PM-MIMO) 1 MUX times 32 AE times 3 branches

BS AE spacing Half wavelengthUserrsquos antenna configuration 1 AE times 3 branches

Number of users 4 for 3D-BF diversity12 for 3D-BF multiplexing

Radius of userrsquos local area (119903UE) 15mAntenna type DipoleModulation QPSK

Number of scatterersOutdoor 4 clusters with 16scatterers per cluster (64 in

total)Scattering sphere radius 10mVelocity of UEs 3 60 and 120 kmhFading Flat

XPD value 58 dB and 97 dB for NLOSand LOS

Correlation 032 and 034 for NLOS andLOS

Rician 119870-factor 9 dB

userrsquos velocities including 3 60 and 120 kmh under theNLOS scenario An extension of other researches [14 31] isapplied to simulations of the polarized MIMO channel forwhich channel characteristics are also listed in Table 1 Wesee that the PACE performance decreases a lot due to highmobility at 60 and 120 kmh which indicates that the numberof pilots is not enough to compensate the channel correctlyin an environment with fast time-varying phase responseThe pilot density is 143 for PACE scheme and by consid-ering the trade-off regarding spectrum efficiency BCE thatrequires no or a minimal number of pilots might be betteremployed Figure 13 additionally shows the performances ofBCE schemes where performance is found that is not relevantto the userrsquos velocity Compared with the BCE reported byNgo and Larsson [29] our proposed BCE performance isbetter because the EVD is based on low correlated submatrixand has less complexity for doing the EVD based on asubmatrix with a smaller size Due to no pilot contaminationby BCE approach the proposed BCE outperforms PACEfor a velocity of 3 kmh when 119864

119887119873

0is less than 25 dB

However BCE has a higher complexity than PACE and itis condition constraint Again according to Figure 13 BCEperforms worse than PACE with a velocity of 3 kmh when119864119887119873

0is larger than 25 dB and the trend of error floor for

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

10minus1

100

UEs

aver

age B

LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

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Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

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Mobile Information Systems 3

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus1

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus11

050

minus05minus1 1

050minus05

minus1

minus1 minus05 0 051 minus1minus050051

XX

ZZ

YY

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus11

Z

(a) 3D beams generated by a triple-polarized ULA system

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus1

1080604020minus02minus04minus06minus08minus11080604020minus02minus04minus06minus08minus11

08

06

04

02

0

minus02

minus04

minus06

minus08

minus1

X X

YY

1

08

06

04

02

0

minus02

minus04

minus06

minus08

minus1

Y

BW8 BW64

(b) Beam-width varied with different number of AEs being employed for example 8 and 64 AEs

Figure 2 3D beams generated by a polarized ULA

index andMUX index respectivelyThe 3D-BF which can beapplied for multipath reception or combination of relay sig-nals [18] is introduced as a promising technique inM-MIMOsystems to enhance the cellular performance by deployingantenna elements in both horizontal and vertical (HampV)dimensions [19] However different from the conventional3D-BF achieved by planar M-MIMO system to control thedowntilted beam in a vertical domain the proposed PM-MIMO realizes the 3D-BF via the linear combination ofpolarized beams It highlights the fact that the 3D-BF not onlyis addressed by theHampV exploration but also can be achievedby antenna polarizationmeanwhile the antenna polarizationalso serves as a pivotal solution dedicated to space constraintin M-MIMO systems

3 Diversity and MultiplexingAchieved by Polarized 3D Beams withan Array Selection Scheme

31 System Architecture Figure 4 describes the architectureof the proposed diversity system via polarized 3D beamswhere the multiple users with each equipping three colocatedantenna branches are considered As studied by Dao et al[17] the cross-array links (eg from BS 119860

11198611and 119860

21198611

to UE 1198611) can be highly correlated by setting the AE

space equal to or less than a half-wavelength The cross-branch links (eg from BS 119860

11198611and 119860

11198612to UE 119861

1) on

the other hand are usually uncorrelated due to the spacepolarizationThis inspired us to incorporate space-time block

4 Mobile Information Systems

MUX-Q

A1B2

A1B1

A1B3

A2B2

A2B3A2B1

APB2

APB1

APB3

MUX-1MUX-2

sQ(t)

X

Y

w12q(t)

w13q(t)

w11q(t)

w22q(t)

w23q(t)

w21q(t)

wP2q(t)

wP3q(t)

wP1q(t)

s2(t)s1(t) S(t)

Figure 3 Structure of the proposed PM-MIMO array system

coding (STBC) and BF techniques simultaneously in theTPULA system to boost performance Moreover in orderto achieve full-rate coding with an odd number of transmitantennae quasi-orthogonal STBC (QO-STBC) has emergedin the literature [20 21] which fully explores diversity gainbut increases the complexity of decoding due to nonorthog-onal interference In this paper the proposed diversityscheme combines QO-STBC for three transmit antennaeand BF techniques via the TPULA system as illustrated inFigure 4

In Figure 4 the BF weights (119908Tx119901119887

) are multiplied beforethe inverse fast Fourier transform (IFFT) block of the BSX

119901in (5) is the transmitted QO-STBC symbol matrix [20]

X119901= (

119909II 119909III 119909IV

119909lowast

I minus119909lowast

IV 119909lowast

III

119909IV 119909I 119909II

119909lowast

III minus119909lowast

II 119909lowast

I

)

119868-by-119869

(5)

where the Roman numeral is the symbol index 119894 is the timeindexmodulo of 4 (119868 = 4) and 119895 is the antenna indexmoduloof 3 (119869 = 3) At each UE the QO-STBC decoding is appliedafter the FFT block at each antenna branch [20] and then we

can have the received signal for each branch of a specific UEbefore QO-STBC decoding as

R119901sim119894thUE

119887

= (h119901sim119894thUE

119887

(WTx119901sim119894thUE

119887

⊙ X119901sim119894thUE

119887

)119879

)

119879

+ n119901sim119894thUE

119887

= (WTx119901sim119894thUE

119887

⊙ X119901sim119894thUE

119887

) h119879119901sim119894thUE

119887

+ n119901sim119894thUE

119887

= (119903119901sim119894thUE

119887I 119903

119901sim119894thUE119887II 119903

119901sim119894thUE119887III 119903

119901sim119894thUE119887IV)

119879

(6)

where ldquo⊙rdquo denotes the Hadamard product and WTx119901

is theTxBF weighting matrix given by

WTx119901sim119894thUE

119887

= (

119908Tx1199011

119908Tx1199012

119908Tx1199013

119908Tx1199011

119908Tx1199012

119908Tx1199013

119908Tx1199011

119908Tx1199012

119908Tx1199013

119908Tx1199011

119908Tx1199012

119908Tx1199013

) (7)

h119901sim119894thUE

119887

is the vector of the polarized cross-branch linksgiven by

h119901sim119894thUE

119887

= (ℎ1199011sim119894thUE

119887

ℎ1199012sim119894thUE

119887

ℎ1199013sim119894thUE

119887) (8)

Mobile Information Systems 5

QO-STBCdecoding

QO-STBCdecoding

QO-STBCdecoding

IFFT and GI extension

GI removal

1st UE

A1B2

A1B1

A1B3

A2B2A2B3

A2B1

A3B2A3B3

A3B1

and FFT

B1

B2

Y

X

qth MUX ofPM-MIMO

APminus2B3

APminus2B2

APminus2B1

APminus1B2

APminus1B1

APminus1B3

APB3

APB2

APB1

wTx12

wTx13

wTx11

wTx22

wTx23

wTx21

wTx32

wTx33

wTx31

wTxP2

wTxP3

wTxP1

wTx(pminus2)2

wTx(pminus2)3

wTx(pminus2)1

wTx(pminus1)2

wTx(pminus1)3

wTx(pminus1)1

B3

B3

B2

B1

Kth UE

EGC

EGC

QO-STBC

QO-STBC

QO-STBCdecoding

QO-STBCdecoding

QO-STBCdecoding

Figure 4 Diversity system architecture by polarized 3D beams

and n119901sim119894thUE

119887

is the noise vector given by

n119901sim119894thUE

119887

= (120590119901sim119894thUE

119887I 120590

119901sim119894thUE119887II 120590

119901sim119894thUE119887III 120590

119901sim119894thUE119887IV)

119879

(9)

The STBC decoding applied thereafter gives

X119901sim119894thUE

119887

= D119901sim119894thUE

119887

Τ119901sim119894thUE

119887

= (119901sim119894thUE

119887I

119901sim119894thUE119887II

119901sim119894thUE119887III

119901sim119894thUE119887IV)

119879

(10)

Here D119901sim119902119887

is the STBC decoding matrix which is modifiedbased on equation (12) in [20] by considering TxBF weights

D119901sim119894thUE

119887

=

((((

(

0 119908Tx1199011

ℎ1199011sim119894thUE

119887

(119908Tx1199012

)lowast

ℎlowast

1199012sim119894thUE

119887

119908Tx1199013

ℎ1199013sim119894thUE

119887

(119908Tx1199011

)lowast

ℎlowast

1199011sim119894thUE

119887

0 (119908Tx1199013

)lowast

ℎlowast

1199013sim119894thUE

119887

minus119908Tx1199012

ℎ1199012sim119894thUE

119887

(119908Tx1199012

)lowast

ℎlowast

1199012sim119894thUE

119887

119908Tx1199013

ℎ1199013sim119894thUE

119887

0 119908Tx1199011

ℎ1199011sim119894thUE

119887

(119908Tx1199013

)lowast

ℎlowast

1199013sim119894thUE

119887

minus119908Tx1199012

ℎ1199012sim119894thUE

119887

(119908Tx1199011

)lowast

ℎlowast

1199011sim119894thUE

119887

0

))))

)

(11)

6 Mobile Information Systems

where Τ119901sim119902119887

is defined as

Τ119901sim119894thUE

119887

= (119901sim119894thUE

119887I

lowast

119901sim119894thUE119887II

119901sim119894thUE119887III

lowast

119901sim119894thUE119887IV)

119879

(12)

by taking the conjugate of the second and the fourth elementsof R

119901sim119894thUE119887

The final output is obtained by the functionalblock of equal gain combining (EGC) as

X

=

3

sum

119887=1

(119901sim119894thUE

119887I

119901sim119894thUE119887II

119901sim119894thUE119887III

119901sim119894thUE119887IV)

119879

(13)

Figure 5 describes the architecture ofmultiplexing systemby polarized 3D beams where each generated beam isdedicated to a piece of UE In this case the data rate is threetimes higher than the 3D-BF diversity system Here we alsoconsider multiple users with each of them equipping threecolocated antenna branches and note that in these two pro-posed schemes the zero-forcing BF is assumed and appliedat transmitter Tx (ie the BS) Compared with diversity casethe proposedmultiplexing scheme is relatively simple that thereceived signal for a specific UE after EGC process can begiven as

R119901sim119894thUE

119887

=

3

sum

119887=1

(h119901sim119894thUE

119887

(WTx119901sim119894thUE

119887

⊙ S119901sim119894thUE

119887

) + n119901sim119894thUE

119887

)

(14)

32 Array Selection Scheme for PM-MIMOArray System Thesharp beam as illustrated in Figure 2(b) performs quite wellin terms of BF interferences mitigation However it is notefficient to assign all AEs of a MUX to form one beamespecially for cell-edge UEs Overall AEs in a MUX can bedivided into several groups to form beams for separate UEsand this part analyses the minimum number of AEs requiredto mitigate BF interferences

Let us have two simultaneous beams point two adjacentpieces of UEs as demonstrated in Figure 6 where 119871 gives thebeam coverage and 119863 and 119889 denote the distance from UE toBS and the distance between the adjacent UEs respectivelyTo make the analysis meaningful we assume that there is asufficient amount of UE deployed in a cell and therewith theUEs are close each other resulting in 119889

1asymp V

1and 119889

2asymp V

2

According to Figure 6 in the case of UE (UE-1 and UE-2)located at a 3 dB beam area that is a half power beam-width(HPBW) area the HPBW needs to be controlled at less than2119889

1to avoid BF interferences On the other hand when UEs

(UE-3 and UE-4) are located at a beam peak area the HPBWcan be set larger than 2119889

2 In addition to assuming that UE is

distributed in a square cell which can be treated as a city blockfor horizontal BF or a building for vertical BF we provideFigure 7 for calculating average 119863 and 119889 Suppose that UEsfollow a spatial Poisson process with an intensity of 120588 so thenumber of UEs in a cell is given as

119870 = 1205881198712

(15)

The average distance between the BS and UE is calculated by

119863 = ∬1198712

1

1198712

119903 119889119903 119889120579

=2

1198712

(int

120603

0

int

119886 cos 120579

0

1199032

119889119903 119889120579 + int

1205872

120603

int

2119886 sin 120579

0

1199032

119889119903 119889120579)

=120585119871

2

(16)

where 120585 = ln(2 + radic5)12 + radic5 minus 2 ln((radic5 minus 1)2)3 asymp 1187The average distance between two adjacent pieces of UEs isgiven as

119889 = ∬119860

1

119860119903119889119903 119889120579 = int

2120587

0

int

119903UE

0

1199032

1205871199032

UE119889119903 119889120579 =

2

3119903UE (17)

where 119860 denotes the local coverage area of UE with a radiusof 119903UE depending on 120588

Because 119863 is calculated close to 1198712 the HPBW lt 2119889

needs to be maintained to avoid BF interferences Accordingto Su and Chang [16] we have

HPBW asymp 2

1003816100381610038161003816100381610038161003816arcsin(1391

120576

120587119875+ sin 120579

0)

1003816100381610038161003816100381610038161003816lt

4

3119903UE (18)

where 120576 denotes the array spacing factor that is 120576 = 120582119904 with119904 and 120582 representing the array spacing and signal wavelengthrespectively 120579

0is the signal incidence angle shifted from

the bore-sight direction and the antenna bore-sight is theaxis vertical to the orientation of the array alignment Forexample if the radius of a userrsquos local area (119903UE) is 15meters atleast 8 AEs are required to avoid BF interferences when 120576 = 2

and 1205790= 1205874 Please note that the above analysis is derived

based on the isotropic array antenna system The requirednumber of AEs may decrease by using the dipole antennabecause it does not radiate in the longitudinal direction ofan antenna structure that maintains a higher radiation gaincompared with the isotropic antenna

As discussed in Su andChang [16] and Liu [22] the beam-width is increased significantly when the beam steers to anangle far off the bore-sight direction such as the case of 120579

0in

(18) reaching 90∘ In order to avoid beam-with extension wepropose a scheme to cope with the large off bore-sight angleby dynamically selecting the set of polarized branches for 3D-BF that can effectivelyworkwithout increasing the dimensionof the array system As depicted in Figure 8 let 120572

119896 120573

119896 and 120574

119896

denote the acute angles corresponding to the119883119884 and119885 axesof the 119896th incident signal we have

120572119896= arcsin

radic1198872

119896

+ 1198882

119896

119863119896

120573119896= arcsin

radic1198862

119896

+ 1198882

119896

119863119896

120574119896= arcsin

radic1198862

119896

+ 1198872

119896

119863119896

(19)

Mobile Information Systems 7

11Tx

w

21Tx

w

31Tx

w

12

Txw

22Tx

w

32

Txw

Yextension

X

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

B1

B2

B3

B1

B2

B3

B1

B2

B3

13

Txw

23Tx

w

33

Txw

A1B2A1B3

A2B3

A3B3

A1B1

A2B2

A2B1

A3B2

A3B1

Kth UE

GI removal and FFTqth MUX of

PM-MIMO

APminus2B3

APminus2B2

APminus2B1

APminus1B2

APminus1B1

APminus1B3

APB3

APB2

APB1

wTxP2

wTxP3

wTxP1

wTx(pminus2)2

wTx(pminus2)3

wTx(pminus2)1

wTx(pminus1)3

wTx(pminus1)2

wTx(pminus1)1

B3

B2

B1

B3

B2

B1

B3

B2

B1

1st UE

2nd UE

3rd UE

(K minus 1)th UE

(K minus 2)th UE

IFFT and GI

Figure 5 Multiplexing system architecture by polarized 3D beams

BS

HPBW

UE-3

UE-4UE-2

UE-1

1

2

L

d1

d2D4

D3

D1

D2

Figure 6 Two beams steer toward two adjacent pieces of UE

8 Mobile Information Systems

UE-2

UE-1D

L

dr

r

UE

120579

minusL2

L2

PM-MIMO

Vertical BF plane

Horizontal BF

120603plane

X

Y

Z

0

Figure 7 Illustration of a square cell used for calculating 119863 and 119889

x

z

y

ck

bk

ak

Dk

120574k

120573k120572k

kth incident signal

PM-MIMO

Figure 8 Selection on the set of branches for 3D-BF via incident signal

where 120572119896 120573

119896 and 120574

119896isin (0 1205872) In order to avoid beam-

width extension by considering the off bore-sight anglethe following criteria need to be carried out for 3D-BFapplications

(i) When 120572119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198613to form the beam for the 119896th incident signal

(ii) When 120573119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198612to form the beam for the 119896th incident signal

(iii) When 120574119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198611to form the beam for the 119896th incident signal

Let 1199101(119905) 119910

2(119905) 119910

119896(119905) denote the incident signal

sequences that come from random directions Figure 9 thenprovides the flowchart of the proposed AE selection schemefor the PM-MIMO system According to Figure 9 the pro-posed scheme at first detects the incident signal sequencesand determines the minimum number of AEs used for 3D-BF via the criterion provided by (18) And then the proposedscheme categorizes the incident signal sequences into threecategories according tomax(120572

119896 120573

119896 120574

119896) For each category the

proposed schemes prepare the set of branches used for 3D-BF via the criteria provided before If the 3D-BF application

is dedicated to the cell-edge users the diversity by usingpolarized 3D beams is employed to maintain the cell-edgeusersrsquo performances Otherwise multiplexing via polarized3D beams is suggested in order to increase overall systemthroughput

4 Blind Channel Estimation to Avoid PilotContamination in PM-MIMO Array System

Theoretically the M-MIMO system is proved to have manyattractive features in wireless communications Howeverthese features are obtained mainly based on the perfectchannel estimation Practically the BS does not have perfectchannel state information that limits the exploration of M-MIMO systems Moreover conventional channel estimationby using training sequences may not be applicable to M-MIMO systems because usually there are tens or hundreds ofantennae applied in M-MIMO systems Spectrum efficiencycould not only be decreased dramatically by reserving manypilots for channel estimation but pilot contamination alsolimits performance because the pilot positions in a resourceblock have to be reused due to massive antenna employment[23ndash26]

Mobile Information Systems 9

No No

No

Start

Detection of incident signalfrom K UEs y1(t) y2(t) yK(t)

For yk(t) find max(120572k 120573k 120574k)

If 120572k is maximum If 120573k is maximum

YesYes

If yA119901B119887k

(t) belongs to cell-edge UE

Select AEs for yA119901B119887k

(t) and explore

diversity gain by STBC with 3D-BF

Select AEs for yA119901B119887k

(t) and explore

multiplexing gain by 3D-BF

k = k + 1

If k gt K

If k gt K

Yes

End

No

Categorize yk(t) to yA119901B3k

(t) max(120572k 120573k 120574k) = 120572k

Categorize yk(t) to yA119901B1k

(t) max(120572k 120573k 120574k) = 120574k

Categorize yk(t) to yA119901B2k

(t) max(120572k 120573k 120574k) = 120573k

Yes

Yes

No

Figure 9 Flowchart of the proposed AE selection scheme for PM-MIMO system

The BCE approach which requires no or a minimalnumber of pilots needs to be applied in M-MIMO systemsOne of the BCE strategies is based on eigenvalue decompo-sition (EVD) for the covariance matrix of a received signalthat needs to preserve pairwise orthogonality among channelvectors [27ndash29] Let us define an M-MIMO system model as

y119896= Hx

119896+ n

119896 (20)

where x119896is the transmitted symbolsH is an119872-by-119873 channel

matrix between the BS and the 119896th UE and n119896denotes

the additive white noise The covariance matrix of thereceived signal is then defined by

Ry119896

≜ y119896y119867119896

= HRx119896

H119867

+ Rn119896

(21)

where 119867 represents the Hermitian Transpose operationAdditionally multiplyingH at both sides of (21) we have

Ry119896

H = HRx119896

H119867H +H (22)

10 Mobile Information Systems

From the law of large number the channel vectors betweenthe BS and the deployed UEs become very long random andpairwise orthogonal which satisfies the condition

1

119872H119867H 997888rarr I

119873 as 119872 997888rarr infin (23)

Thereafter the estimated channel can be obtained as theeigenvectors of Ry

119896

via EVD processing [29]Note that since we focus on the link-level performance

the element of channel matrix H should be normalized andonly the additive noise and fast fading effects are taken intoconsideration to generate H If the array spacing is largerthan a half wave-length the elements of H would be lowlycorrelated and then the condition of (23) is easy to be satisfiedas reported elsewhere [30] where the BS AEs are usually sep-arated by several wave-lengths resulting in an uncorrelatedTx radiation pattern to preserve the pairwise orthogonalityamong channel vectors However in space-limitedM-MIMOsystems the pairwise orthogonality cannot be maintainedbecause the adjacent AE space is fixed normally at equal

or less than a half signal wave-length Consequently in thispaper we modify the EVD-based blind channel estimationscheme studied in Ngo and Larsson [29] The modifiedBCE approach can exploit the pairwise orthogonality via theparticular characteristics of PM-MIMO systems that is thepolarized cross-branch links in the system usually are uncor-related even though the adjacent AE spacing is set equal toor less than a half signal wave-length [17]

Based on other researches [14 16 31] an extension of thechannel matrix for PM-MIMO systems can be represented as

HPM-MIMO (119905)

= (

hTx1198601minusRx119860

1(119905) sdot sdot sdot hTx119860

1minusRx119860

(119905)

d

hTx119860119875minusRx119860

1(119905) sdot sdot sdot hTx119860

119875minusRx119860

(119905)

)

(24)

where

hTx119860119901minusRx119860

(119905) = radic

120578

119868

119868

sum

119894=1

(

ℎTx1198601199011198611minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198611(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198612(119905) ℎTx119860

1199011198612minusRx119860

1198612(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198612(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198613(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198613(119905) ℎTx119860

1199011198613minusRx119860

1198613(119905)

) (25)

Here 120578 and 119868 denote the transmit power and the numberof scatterers respectively Channel matrix (24) has a size of3119875-by-3 which is composed of 3-by-3 submatrices Eachsubmatrix holds the polarized cross-branch links between the119875th AE of Tx (the BS) and the th AE (UE) of receiver (Rx)Please note that throughout the paper theUE is assumedwithone AE that is = 1 The channel vectors of submatrix(25) are random and pairwise orthogonal because the polar-ized links from a Tx AE with three orthogonal branches toa single Rx branch are usually highly orthogonal [17] Con-sequently we can apply the EVD-based BCE via submatrixof (25) By redefining the covariance matrix of the receivedsignal as

Ry119896

≜ y119896y119867119896

= hTx119860119901minusRx119860

Rx119896

h119867Tx119860119901minusRx119860

+ Rn119896

(26)

the estimated channel can be obtained as the eigenvec-tors of Ry

119896

via EVD processing because the condition of(13)h119867Tx119860

119901minusRx119860

hTx119860119901minusRx119860

rarr I3is satisfied

5 Performance Verification

Table 1 lists the parameters settings of the performance veri-fication based on the LTE-A specification [32] The downlinkdata mapping for LTE-A resource blocks used in simulationsis demonstrated in Figure 10 which is based on theQO-STBC

symbol matrix of (5)We use the training sequences providedby [32] which are defined as

119903119897119899119904(119898) =

1

radic2(1 minus 2 sdot 119888 (2119898))

+ 1198951

radic2(1 minus 2 sdot 119888 (2119898 + 1))

(27)

where 119898 = 0 1 2119873max119863119871

119877119861

minus 1 The pilot density is 143and the initialization of 119888 is defined as

119888init = 210

sdot (7 sdot (119899119904+ 1) + 119897 + 1) sdot (2 sdot 119873

cellID + 1) + 2

sdot 119873cellID + 119873CP

(28)

where 119899119904is the slot number within a frame and

119873CP =

1 for normal CP

0 for extended CP(29)

Figure 11 depicts the probability densities of the HPBWgenerated in simulations where the HPBW can be effectivelykept as 50∘ on average by using the proposed AE selectionscheme of Figure 9 However the average HPBW extends byabout 15∘ when not considering the off bore-sight angle effectThis demonstrates that the proposed AE selection scheme isrobust that can optimize the generated beamwidth to avoidBF interference

Mobile Information Systems 11

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Branch A1B1 Branch A2B1

(a) Data mapping at Tx1198601199011198611

minus

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98765432

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20 1 3 4 5 6 7 8 9Subframe

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Branch A1B2 Branch A2B2

(b) Data mapping at Tx1198601199011198612

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ck

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98765432

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13121110

Branch A2B3

PA2B3PA2B3

PA2B3 PA2B3

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98765432

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Branch A1B3

(c) Data mapping at Tx1198601199011198613

Figure 10 Downlink data mapping of the LTE-A resource blocks used in the simulation

12 Mobile Information Systems

90

0005

001

0015

002

0025

003

With the proposed AE selection schemeWithout the proposed AE selection scheme

30 40 50 60 70 800

HPBW (deg)

Figure 11 Probability density of HPBW

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300

Case 2 PACE outdoor LOS 3kmhCase 3 PACE outdoor LOS 3kmh

Case 1 PACE outdoor LOS 3kmhCase 3 PACE outdoor NLOS 3kmhCase 2 PACE outdoor NLOS 3kmhCase 1 PACE outdoor NLOS 3kmh

EbN0 (dB)

Figure 12Users average BLERperformances based on the proposeddiversity system architecture

Figure 12 compares the usersrsquo average block error rate(BLER) performances obtained based on the proposeddiversity system architecture by using different transmissionschemes including Case 1 without STBC and TxBF Case2 with STBC only and Case 3 with STBC and TxBF viathe LTE pilot-assistant practical channel estimation (PACE)approach According to Figure 12 Case 1 has the worstperformance because there is no space-time coding and BFgain achieved About 17 dB of signal-to-noise ratio (SNR)gain at the target BLER can be achieved by Case 2 comparedwith Case 1 under the non-line-of-sight NLOS scenarioThere is about a 1 dB SNR gain that can be further achievedby employing the TxBF of Case 3 In addition the simulationresults under the LOS scenario are also provided as acomparison where almost 7 dB gain can be obtained whenthe LOS exists for those three cases

Next we simulate the BCE approaches and compare itsefficiency with the PACE based on the proposed diversitysystemarchitecture Figure 13 demonstrates the usersrsquo averageBLER via PACE and BCE approaches for three different

Table 1 Simulation parameters

Parameters ValueCarrier frequency 18GHzSystem bandwidth 20MHzFFT size 2048Number of data carriers 1200Number of samples in CP 144Subcarrier spacing 15 kHzBS antenna configuration(PM-MIMO) 1 MUX times 32 AE times 3 branches

BS AE spacing Half wavelengthUserrsquos antenna configuration 1 AE times 3 branches

Number of users 4 for 3D-BF diversity12 for 3D-BF multiplexing

Radius of userrsquos local area (119903UE) 15mAntenna type DipoleModulation QPSK

Number of scatterersOutdoor 4 clusters with 16scatterers per cluster (64 in

total)Scattering sphere radius 10mVelocity of UEs 3 60 and 120 kmhFading Flat

XPD value 58 dB and 97 dB for NLOSand LOS

Correlation 032 and 034 for NLOS andLOS

Rician 119870-factor 9 dB

userrsquos velocities including 3 60 and 120 kmh under theNLOS scenario An extension of other researches [14 31] isapplied to simulations of the polarized MIMO channel forwhich channel characteristics are also listed in Table 1 Wesee that the PACE performance decreases a lot due to highmobility at 60 and 120 kmh which indicates that the numberof pilots is not enough to compensate the channel correctlyin an environment with fast time-varying phase responseThe pilot density is 143 for PACE scheme and by consid-ering the trade-off regarding spectrum efficiency BCE thatrequires no or a minimal number of pilots might be betteremployed Figure 13 additionally shows the performances ofBCE schemes where performance is found that is not relevantto the userrsquos velocity Compared with the BCE reported byNgo and Larsson [29] our proposed BCE performance isbetter because the EVD is based on low correlated submatrixand has less complexity for doing the EVD based on asubmatrix with a smaller size Due to no pilot contaminationby BCE approach the proposed BCE outperforms PACEfor a velocity of 3 kmh when 119864

119887119873

0is less than 25 dB

However BCE has a higher complexity than PACE and itis condition constraint Again according to Figure 13 BCEperforms worse than PACE with a velocity of 3 kmh when119864119887119873

0is larger than 25 dB and the trend of error floor for

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

10minus1

100

UEs

aver

age B

LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

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International Journal of

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Distributed Sensor Networks

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Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

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International Journal of

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

Advances in

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RoboticsJournal of

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

4 Mobile Information Systems

MUX-Q

A1B2

A1B1

A1B3

A2B2

A2B3A2B1

APB2

APB1

APB3

MUX-1MUX-2

sQ(t)

X

Y

w12q(t)

w13q(t)

w11q(t)

w22q(t)

w23q(t)

w21q(t)

wP2q(t)

wP3q(t)

wP1q(t)

s2(t)s1(t) S(t)

Figure 3 Structure of the proposed PM-MIMO array system

coding (STBC) and BF techniques simultaneously in theTPULA system to boost performance Moreover in orderto achieve full-rate coding with an odd number of transmitantennae quasi-orthogonal STBC (QO-STBC) has emergedin the literature [20 21] which fully explores diversity gainbut increases the complexity of decoding due to nonorthog-onal interference In this paper the proposed diversityscheme combines QO-STBC for three transmit antennaeand BF techniques via the TPULA system as illustrated inFigure 4

In Figure 4 the BF weights (119908Tx119901119887

) are multiplied beforethe inverse fast Fourier transform (IFFT) block of the BSX

119901in (5) is the transmitted QO-STBC symbol matrix [20]

X119901= (

119909II 119909III 119909IV

119909lowast

I minus119909lowast

IV 119909lowast

III

119909IV 119909I 119909II

119909lowast

III minus119909lowast

II 119909lowast

I

)

119868-by-119869

(5)

where the Roman numeral is the symbol index 119894 is the timeindexmodulo of 4 (119868 = 4) and 119895 is the antenna indexmoduloof 3 (119869 = 3) At each UE the QO-STBC decoding is appliedafter the FFT block at each antenna branch [20] and then we

can have the received signal for each branch of a specific UEbefore QO-STBC decoding as

R119901sim119894thUE

119887

= (h119901sim119894thUE

119887

(WTx119901sim119894thUE

119887

⊙ X119901sim119894thUE

119887

)119879

)

119879

+ n119901sim119894thUE

119887

= (WTx119901sim119894thUE

119887

⊙ X119901sim119894thUE

119887

) h119879119901sim119894thUE

119887

+ n119901sim119894thUE

119887

= (119903119901sim119894thUE

119887I 119903

119901sim119894thUE119887II 119903

119901sim119894thUE119887III 119903

119901sim119894thUE119887IV)

119879

(6)

where ldquo⊙rdquo denotes the Hadamard product and WTx119901

is theTxBF weighting matrix given by

WTx119901sim119894thUE

119887

= (

119908Tx1199011

119908Tx1199012

119908Tx1199013

119908Tx1199011

119908Tx1199012

119908Tx1199013

119908Tx1199011

119908Tx1199012

119908Tx1199013

119908Tx1199011

119908Tx1199012

119908Tx1199013

) (7)

h119901sim119894thUE

119887

is the vector of the polarized cross-branch linksgiven by

h119901sim119894thUE

119887

= (ℎ1199011sim119894thUE

119887

ℎ1199012sim119894thUE

119887

ℎ1199013sim119894thUE

119887) (8)

Mobile Information Systems 5

QO-STBCdecoding

QO-STBCdecoding

QO-STBCdecoding

IFFT and GI extension

GI removal

1st UE

A1B2

A1B1

A1B3

A2B2A2B3

A2B1

A3B2A3B3

A3B1

and FFT

B1

B2

Y

X

qth MUX ofPM-MIMO

APminus2B3

APminus2B2

APminus2B1

APminus1B2

APminus1B1

APminus1B3

APB3

APB2

APB1

wTx12

wTx13

wTx11

wTx22

wTx23

wTx21

wTx32

wTx33

wTx31

wTxP2

wTxP3

wTxP1

wTx(pminus2)2

wTx(pminus2)3

wTx(pminus2)1

wTx(pminus1)2

wTx(pminus1)3

wTx(pminus1)1

B3

B3

B2

B1

Kth UE

EGC

EGC

QO-STBC

QO-STBC

QO-STBCdecoding

QO-STBCdecoding

QO-STBCdecoding

Figure 4 Diversity system architecture by polarized 3D beams

and n119901sim119894thUE

119887

is the noise vector given by

n119901sim119894thUE

119887

= (120590119901sim119894thUE

119887I 120590

119901sim119894thUE119887II 120590

119901sim119894thUE119887III 120590

119901sim119894thUE119887IV)

119879

(9)

The STBC decoding applied thereafter gives

X119901sim119894thUE

119887

= D119901sim119894thUE

119887

Τ119901sim119894thUE

119887

= (119901sim119894thUE

119887I

119901sim119894thUE119887II

119901sim119894thUE119887III

119901sim119894thUE119887IV)

119879

(10)

Here D119901sim119902119887

is the STBC decoding matrix which is modifiedbased on equation (12) in [20] by considering TxBF weights

D119901sim119894thUE

119887

=

((((

(

0 119908Tx1199011

ℎ1199011sim119894thUE

119887

(119908Tx1199012

)lowast

ℎlowast

1199012sim119894thUE

119887

119908Tx1199013

ℎ1199013sim119894thUE

119887

(119908Tx1199011

)lowast

ℎlowast

1199011sim119894thUE

119887

0 (119908Tx1199013

)lowast

ℎlowast

1199013sim119894thUE

119887

minus119908Tx1199012

ℎ1199012sim119894thUE

119887

(119908Tx1199012

)lowast

ℎlowast

1199012sim119894thUE

119887

119908Tx1199013

ℎ1199013sim119894thUE

119887

0 119908Tx1199011

ℎ1199011sim119894thUE

119887

(119908Tx1199013

)lowast

ℎlowast

1199013sim119894thUE

119887

minus119908Tx1199012

ℎ1199012sim119894thUE

119887

(119908Tx1199011

)lowast

ℎlowast

1199011sim119894thUE

119887

0

))))

)

(11)

6 Mobile Information Systems

where Τ119901sim119902119887

is defined as

Τ119901sim119894thUE

119887

= (119901sim119894thUE

119887I

lowast

119901sim119894thUE119887II

119901sim119894thUE119887III

lowast

119901sim119894thUE119887IV)

119879

(12)

by taking the conjugate of the second and the fourth elementsof R

119901sim119894thUE119887

The final output is obtained by the functionalblock of equal gain combining (EGC) as

X

=

3

sum

119887=1

(119901sim119894thUE

119887I

119901sim119894thUE119887II

119901sim119894thUE119887III

119901sim119894thUE119887IV)

119879

(13)

Figure 5 describes the architecture ofmultiplexing systemby polarized 3D beams where each generated beam isdedicated to a piece of UE In this case the data rate is threetimes higher than the 3D-BF diversity system Here we alsoconsider multiple users with each of them equipping threecolocated antenna branches and note that in these two pro-posed schemes the zero-forcing BF is assumed and appliedat transmitter Tx (ie the BS) Compared with diversity casethe proposedmultiplexing scheme is relatively simple that thereceived signal for a specific UE after EGC process can begiven as

R119901sim119894thUE

119887

=

3

sum

119887=1

(h119901sim119894thUE

119887

(WTx119901sim119894thUE

119887

⊙ S119901sim119894thUE

119887

) + n119901sim119894thUE

119887

)

(14)

32 Array Selection Scheme for PM-MIMOArray System Thesharp beam as illustrated in Figure 2(b) performs quite wellin terms of BF interferences mitigation However it is notefficient to assign all AEs of a MUX to form one beamespecially for cell-edge UEs Overall AEs in a MUX can bedivided into several groups to form beams for separate UEsand this part analyses the minimum number of AEs requiredto mitigate BF interferences

Let us have two simultaneous beams point two adjacentpieces of UEs as demonstrated in Figure 6 where 119871 gives thebeam coverage and 119863 and 119889 denote the distance from UE toBS and the distance between the adjacent UEs respectivelyTo make the analysis meaningful we assume that there is asufficient amount of UE deployed in a cell and therewith theUEs are close each other resulting in 119889

1asymp V

1and 119889

2asymp V

2

According to Figure 6 in the case of UE (UE-1 and UE-2)located at a 3 dB beam area that is a half power beam-width(HPBW) area the HPBW needs to be controlled at less than2119889

1to avoid BF interferences On the other hand when UEs

(UE-3 and UE-4) are located at a beam peak area the HPBWcan be set larger than 2119889

2 In addition to assuming that UE is

distributed in a square cell which can be treated as a city blockfor horizontal BF or a building for vertical BF we provideFigure 7 for calculating average 119863 and 119889 Suppose that UEsfollow a spatial Poisson process with an intensity of 120588 so thenumber of UEs in a cell is given as

119870 = 1205881198712

(15)

The average distance between the BS and UE is calculated by

119863 = ∬1198712

1

1198712

119903 119889119903 119889120579

=2

1198712

(int

120603

0

int

119886 cos 120579

0

1199032

119889119903 119889120579 + int

1205872

120603

int

2119886 sin 120579

0

1199032

119889119903 119889120579)

=120585119871

2

(16)

where 120585 = ln(2 + radic5)12 + radic5 minus 2 ln((radic5 minus 1)2)3 asymp 1187The average distance between two adjacent pieces of UEs isgiven as

119889 = ∬119860

1

119860119903119889119903 119889120579 = int

2120587

0

int

119903UE

0

1199032

1205871199032

UE119889119903 119889120579 =

2

3119903UE (17)

where 119860 denotes the local coverage area of UE with a radiusof 119903UE depending on 120588

Because 119863 is calculated close to 1198712 the HPBW lt 2119889

needs to be maintained to avoid BF interferences Accordingto Su and Chang [16] we have

HPBW asymp 2

1003816100381610038161003816100381610038161003816arcsin(1391

120576

120587119875+ sin 120579

0)

1003816100381610038161003816100381610038161003816lt

4

3119903UE (18)

where 120576 denotes the array spacing factor that is 120576 = 120582119904 with119904 and 120582 representing the array spacing and signal wavelengthrespectively 120579

0is the signal incidence angle shifted from

the bore-sight direction and the antenna bore-sight is theaxis vertical to the orientation of the array alignment Forexample if the radius of a userrsquos local area (119903UE) is 15meters atleast 8 AEs are required to avoid BF interferences when 120576 = 2

and 1205790= 1205874 Please note that the above analysis is derived

based on the isotropic array antenna system The requirednumber of AEs may decrease by using the dipole antennabecause it does not radiate in the longitudinal direction ofan antenna structure that maintains a higher radiation gaincompared with the isotropic antenna

As discussed in Su andChang [16] and Liu [22] the beam-width is increased significantly when the beam steers to anangle far off the bore-sight direction such as the case of 120579

0in

(18) reaching 90∘ In order to avoid beam-with extension wepropose a scheme to cope with the large off bore-sight angleby dynamically selecting the set of polarized branches for 3D-BF that can effectivelyworkwithout increasing the dimensionof the array system As depicted in Figure 8 let 120572

119896 120573

119896 and 120574

119896

denote the acute angles corresponding to the119883119884 and119885 axesof the 119896th incident signal we have

120572119896= arcsin

radic1198872

119896

+ 1198882

119896

119863119896

120573119896= arcsin

radic1198862

119896

+ 1198882

119896

119863119896

120574119896= arcsin

radic1198862

119896

+ 1198872

119896

119863119896

(19)

Mobile Information Systems 7

11Tx

w

21Tx

w

31Tx

w

12

Txw

22Tx

w

32

Txw

Yextension

X

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

B1

B2

B3

B1

B2

B3

B1

B2

B3

13

Txw

23Tx

w

33

Txw

A1B2A1B3

A2B3

A3B3

A1B1

A2B2

A2B1

A3B2

A3B1

Kth UE

GI removal and FFTqth MUX of

PM-MIMO

APminus2B3

APminus2B2

APminus2B1

APminus1B2

APminus1B1

APminus1B3

APB3

APB2

APB1

wTxP2

wTxP3

wTxP1

wTx(pminus2)2

wTx(pminus2)3

wTx(pminus2)1

wTx(pminus1)3

wTx(pminus1)2

wTx(pminus1)1

B3

B2

B1

B3

B2

B1

B3

B2

B1

1st UE

2nd UE

3rd UE

(K minus 1)th UE

(K minus 2)th UE

IFFT and GI

Figure 5 Multiplexing system architecture by polarized 3D beams

BS

HPBW

UE-3

UE-4UE-2

UE-1

1

2

L

d1

d2D4

D3

D1

D2

Figure 6 Two beams steer toward two adjacent pieces of UE

8 Mobile Information Systems

UE-2

UE-1D

L

dr

r

UE

120579

minusL2

L2

PM-MIMO

Vertical BF plane

Horizontal BF

120603plane

X

Y

Z

0

Figure 7 Illustration of a square cell used for calculating 119863 and 119889

x

z

y

ck

bk

ak

Dk

120574k

120573k120572k

kth incident signal

PM-MIMO

Figure 8 Selection on the set of branches for 3D-BF via incident signal

where 120572119896 120573

119896 and 120574

119896isin (0 1205872) In order to avoid beam-

width extension by considering the off bore-sight anglethe following criteria need to be carried out for 3D-BFapplications

(i) When 120572119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198613to form the beam for the 119896th incident signal

(ii) When 120573119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198612to form the beam for the 119896th incident signal

(iii) When 120574119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198611to form the beam for the 119896th incident signal

Let 1199101(119905) 119910

2(119905) 119910

119896(119905) denote the incident signal

sequences that come from random directions Figure 9 thenprovides the flowchart of the proposed AE selection schemefor the PM-MIMO system According to Figure 9 the pro-posed scheme at first detects the incident signal sequencesand determines the minimum number of AEs used for 3D-BF via the criterion provided by (18) And then the proposedscheme categorizes the incident signal sequences into threecategories according tomax(120572

119896 120573

119896 120574

119896) For each category the

proposed schemes prepare the set of branches used for 3D-BF via the criteria provided before If the 3D-BF application

is dedicated to the cell-edge users the diversity by usingpolarized 3D beams is employed to maintain the cell-edgeusersrsquo performances Otherwise multiplexing via polarized3D beams is suggested in order to increase overall systemthroughput

4 Blind Channel Estimation to Avoid PilotContamination in PM-MIMO Array System

Theoretically the M-MIMO system is proved to have manyattractive features in wireless communications Howeverthese features are obtained mainly based on the perfectchannel estimation Practically the BS does not have perfectchannel state information that limits the exploration of M-MIMO systems Moreover conventional channel estimationby using training sequences may not be applicable to M-MIMO systems because usually there are tens or hundreds ofantennae applied in M-MIMO systems Spectrum efficiencycould not only be decreased dramatically by reserving manypilots for channel estimation but pilot contamination alsolimits performance because the pilot positions in a resourceblock have to be reused due to massive antenna employment[23ndash26]

Mobile Information Systems 9

No No

No

Start

Detection of incident signalfrom K UEs y1(t) y2(t) yK(t)

For yk(t) find max(120572k 120573k 120574k)

If 120572k is maximum If 120573k is maximum

YesYes

If yA119901B119887k

(t) belongs to cell-edge UE

Select AEs for yA119901B119887k

(t) and explore

diversity gain by STBC with 3D-BF

Select AEs for yA119901B119887k

(t) and explore

multiplexing gain by 3D-BF

k = k + 1

If k gt K

If k gt K

Yes

End

No

Categorize yk(t) to yA119901B3k

(t) max(120572k 120573k 120574k) = 120572k

Categorize yk(t) to yA119901B1k

(t) max(120572k 120573k 120574k) = 120574k

Categorize yk(t) to yA119901B2k

(t) max(120572k 120573k 120574k) = 120573k

Yes

Yes

No

Figure 9 Flowchart of the proposed AE selection scheme for PM-MIMO system

The BCE approach which requires no or a minimalnumber of pilots needs to be applied in M-MIMO systemsOne of the BCE strategies is based on eigenvalue decompo-sition (EVD) for the covariance matrix of a received signalthat needs to preserve pairwise orthogonality among channelvectors [27ndash29] Let us define an M-MIMO system model as

y119896= Hx

119896+ n

119896 (20)

where x119896is the transmitted symbolsH is an119872-by-119873 channel

matrix between the BS and the 119896th UE and n119896denotes

the additive white noise The covariance matrix of thereceived signal is then defined by

Ry119896

≜ y119896y119867119896

= HRx119896

H119867

+ Rn119896

(21)

where 119867 represents the Hermitian Transpose operationAdditionally multiplyingH at both sides of (21) we have

Ry119896

H = HRx119896

H119867H +H (22)

10 Mobile Information Systems

From the law of large number the channel vectors betweenthe BS and the deployed UEs become very long random andpairwise orthogonal which satisfies the condition

1

119872H119867H 997888rarr I

119873 as 119872 997888rarr infin (23)

Thereafter the estimated channel can be obtained as theeigenvectors of Ry

119896

via EVD processing [29]Note that since we focus on the link-level performance

the element of channel matrix H should be normalized andonly the additive noise and fast fading effects are taken intoconsideration to generate H If the array spacing is largerthan a half wave-length the elements of H would be lowlycorrelated and then the condition of (23) is easy to be satisfiedas reported elsewhere [30] where the BS AEs are usually sep-arated by several wave-lengths resulting in an uncorrelatedTx radiation pattern to preserve the pairwise orthogonalityamong channel vectors However in space-limitedM-MIMOsystems the pairwise orthogonality cannot be maintainedbecause the adjacent AE space is fixed normally at equal

or less than a half signal wave-length Consequently in thispaper we modify the EVD-based blind channel estimationscheme studied in Ngo and Larsson [29] The modifiedBCE approach can exploit the pairwise orthogonality via theparticular characteristics of PM-MIMO systems that is thepolarized cross-branch links in the system usually are uncor-related even though the adjacent AE spacing is set equal toor less than a half signal wave-length [17]

Based on other researches [14 16 31] an extension of thechannel matrix for PM-MIMO systems can be represented as

HPM-MIMO (119905)

= (

hTx1198601minusRx119860

1(119905) sdot sdot sdot hTx119860

1minusRx119860

(119905)

d

hTx119860119875minusRx119860

1(119905) sdot sdot sdot hTx119860

119875minusRx119860

(119905)

)

(24)

where

hTx119860119901minusRx119860

(119905) = radic

120578

119868

119868

sum

119894=1

(

ℎTx1198601199011198611minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198611(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198612(119905) ℎTx119860

1199011198612minusRx119860

1198612(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198612(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198613(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198613(119905) ℎTx119860

1199011198613minusRx119860

1198613(119905)

) (25)

Here 120578 and 119868 denote the transmit power and the numberof scatterers respectively Channel matrix (24) has a size of3119875-by-3 which is composed of 3-by-3 submatrices Eachsubmatrix holds the polarized cross-branch links between the119875th AE of Tx (the BS) and the th AE (UE) of receiver (Rx)Please note that throughout the paper theUE is assumedwithone AE that is = 1 The channel vectors of submatrix(25) are random and pairwise orthogonal because the polar-ized links from a Tx AE with three orthogonal branches toa single Rx branch are usually highly orthogonal [17] Con-sequently we can apply the EVD-based BCE via submatrixof (25) By redefining the covariance matrix of the receivedsignal as

Ry119896

≜ y119896y119867119896

= hTx119860119901minusRx119860

Rx119896

h119867Tx119860119901minusRx119860

+ Rn119896

(26)

the estimated channel can be obtained as the eigenvec-tors of Ry

119896

via EVD processing because the condition of(13)h119867Tx119860

119901minusRx119860

hTx119860119901minusRx119860

rarr I3is satisfied

5 Performance Verification

Table 1 lists the parameters settings of the performance veri-fication based on the LTE-A specification [32] The downlinkdata mapping for LTE-A resource blocks used in simulationsis demonstrated in Figure 10 which is based on theQO-STBC

symbol matrix of (5)We use the training sequences providedby [32] which are defined as

119903119897119899119904(119898) =

1

radic2(1 minus 2 sdot 119888 (2119898))

+ 1198951

radic2(1 minus 2 sdot 119888 (2119898 + 1))

(27)

where 119898 = 0 1 2119873max119863119871

119877119861

minus 1 The pilot density is 143and the initialization of 119888 is defined as

119888init = 210

sdot (7 sdot (119899119904+ 1) + 119897 + 1) sdot (2 sdot 119873

cellID + 1) + 2

sdot 119873cellID + 119873CP

(28)

where 119899119904is the slot number within a frame and

119873CP =

1 for normal CP

0 for extended CP(29)

Figure 11 depicts the probability densities of the HPBWgenerated in simulations where the HPBW can be effectivelykept as 50∘ on average by using the proposed AE selectionscheme of Figure 9 However the average HPBW extends byabout 15∘ when not considering the off bore-sight angle effectThis demonstrates that the proposed AE selection scheme isrobust that can optimize the generated beamwidth to avoidBF interference

Mobile Information Systems 11

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Branch A1B1 Branch A2B1

(a) Data mapping at Tx1198601199011198611

minus

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1110

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Branch A1B2 Branch A2B2

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Branch A1B3

(c) Data mapping at Tx1198601199011198613

Figure 10 Downlink data mapping of the LTE-A resource blocks used in the simulation

12 Mobile Information Systems

90

0005

001

0015

002

0025

003

With the proposed AE selection schemeWithout the proposed AE selection scheme

30 40 50 60 70 800

HPBW (deg)

Figure 11 Probability density of HPBW

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300

Case 2 PACE outdoor LOS 3kmhCase 3 PACE outdoor LOS 3kmh

Case 1 PACE outdoor LOS 3kmhCase 3 PACE outdoor NLOS 3kmhCase 2 PACE outdoor NLOS 3kmhCase 1 PACE outdoor NLOS 3kmh

EbN0 (dB)

Figure 12Users average BLERperformances based on the proposeddiversity system architecture

Figure 12 compares the usersrsquo average block error rate(BLER) performances obtained based on the proposeddiversity system architecture by using different transmissionschemes including Case 1 without STBC and TxBF Case2 with STBC only and Case 3 with STBC and TxBF viathe LTE pilot-assistant practical channel estimation (PACE)approach According to Figure 12 Case 1 has the worstperformance because there is no space-time coding and BFgain achieved About 17 dB of signal-to-noise ratio (SNR)gain at the target BLER can be achieved by Case 2 comparedwith Case 1 under the non-line-of-sight NLOS scenarioThere is about a 1 dB SNR gain that can be further achievedby employing the TxBF of Case 3 In addition the simulationresults under the LOS scenario are also provided as acomparison where almost 7 dB gain can be obtained whenthe LOS exists for those three cases

Next we simulate the BCE approaches and compare itsefficiency with the PACE based on the proposed diversitysystemarchitecture Figure 13 demonstrates the usersrsquo averageBLER via PACE and BCE approaches for three different

Table 1 Simulation parameters

Parameters ValueCarrier frequency 18GHzSystem bandwidth 20MHzFFT size 2048Number of data carriers 1200Number of samples in CP 144Subcarrier spacing 15 kHzBS antenna configuration(PM-MIMO) 1 MUX times 32 AE times 3 branches

BS AE spacing Half wavelengthUserrsquos antenna configuration 1 AE times 3 branches

Number of users 4 for 3D-BF diversity12 for 3D-BF multiplexing

Radius of userrsquos local area (119903UE) 15mAntenna type DipoleModulation QPSK

Number of scatterersOutdoor 4 clusters with 16scatterers per cluster (64 in

total)Scattering sphere radius 10mVelocity of UEs 3 60 and 120 kmhFading Flat

XPD value 58 dB and 97 dB for NLOSand LOS

Correlation 032 and 034 for NLOS andLOS

Rician 119870-factor 9 dB

userrsquos velocities including 3 60 and 120 kmh under theNLOS scenario An extension of other researches [14 31] isapplied to simulations of the polarized MIMO channel forwhich channel characteristics are also listed in Table 1 Wesee that the PACE performance decreases a lot due to highmobility at 60 and 120 kmh which indicates that the numberof pilots is not enough to compensate the channel correctlyin an environment with fast time-varying phase responseThe pilot density is 143 for PACE scheme and by consid-ering the trade-off regarding spectrum efficiency BCE thatrequires no or a minimal number of pilots might be betteremployed Figure 13 additionally shows the performances ofBCE schemes where performance is found that is not relevantto the userrsquos velocity Compared with the BCE reported byNgo and Larsson [29] our proposed BCE performance isbetter because the EVD is based on low correlated submatrixand has less complexity for doing the EVD based on asubmatrix with a smaller size Due to no pilot contaminationby BCE approach the proposed BCE outperforms PACEfor a velocity of 3 kmh when 119864

119887119873

0is less than 25 dB

However BCE has a higher complexity than PACE and itis condition constraint Again according to Figure 13 BCEperforms worse than PACE with a velocity of 3 kmh when119864119887119873

0is larger than 25 dB and the trend of error floor for

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

10minus1

100

UEs

aver

age B

LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

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International Journal of

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

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RoboticsJournal of

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mobile Information Systems 5

QO-STBCdecoding

QO-STBCdecoding

QO-STBCdecoding

IFFT and GI extension

GI removal

1st UE

A1B2

A1B1

A1B3

A2B2A2B3

A2B1

A3B2A3B3

A3B1

and FFT

B1

B2

Y

X

qth MUX ofPM-MIMO

APminus2B3

APminus2B2

APminus2B1

APminus1B2

APminus1B1

APminus1B3

APB3

APB2

APB1

wTx12

wTx13

wTx11

wTx22

wTx23

wTx21

wTx32

wTx33

wTx31

wTxP2

wTxP3

wTxP1

wTx(pminus2)2

wTx(pminus2)3

wTx(pminus2)1

wTx(pminus1)2

wTx(pminus1)3

wTx(pminus1)1

B3

B3

B2

B1

Kth UE

EGC

EGC

QO-STBC

QO-STBC

QO-STBCdecoding

QO-STBCdecoding

QO-STBCdecoding

Figure 4 Diversity system architecture by polarized 3D beams

and n119901sim119894thUE

119887

is the noise vector given by

n119901sim119894thUE

119887

= (120590119901sim119894thUE

119887I 120590

119901sim119894thUE119887II 120590

119901sim119894thUE119887III 120590

119901sim119894thUE119887IV)

119879

(9)

The STBC decoding applied thereafter gives

X119901sim119894thUE

119887

= D119901sim119894thUE

119887

Τ119901sim119894thUE

119887

= (119901sim119894thUE

119887I

119901sim119894thUE119887II

119901sim119894thUE119887III

119901sim119894thUE119887IV)

119879

(10)

Here D119901sim119902119887

is the STBC decoding matrix which is modifiedbased on equation (12) in [20] by considering TxBF weights

D119901sim119894thUE

119887

=

((((

(

0 119908Tx1199011

ℎ1199011sim119894thUE

119887

(119908Tx1199012

)lowast

ℎlowast

1199012sim119894thUE

119887

119908Tx1199013

ℎ1199013sim119894thUE

119887

(119908Tx1199011

)lowast

ℎlowast

1199011sim119894thUE

119887

0 (119908Tx1199013

)lowast

ℎlowast

1199013sim119894thUE

119887

minus119908Tx1199012

ℎ1199012sim119894thUE

119887

(119908Tx1199012

)lowast

ℎlowast

1199012sim119894thUE

119887

119908Tx1199013

ℎ1199013sim119894thUE

119887

0 119908Tx1199011

ℎ1199011sim119894thUE

119887

(119908Tx1199013

)lowast

ℎlowast

1199013sim119894thUE

119887

minus119908Tx1199012

ℎ1199012sim119894thUE

119887

(119908Tx1199011

)lowast

ℎlowast

1199011sim119894thUE

119887

0

))))

)

(11)

6 Mobile Information Systems

where Τ119901sim119902119887

is defined as

Τ119901sim119894thUE

119887

= (119901sim119894thUE

119887I

lowast

119901sim119894thUE119887II

119901sim119894thUE119887III

lowast

119901sim119894thUE119887IV)

119879

(12)

by taking the conjugate of the second and the fourth elementsof R

119901sim119894thUE119887

The final output is obtained by the functionalblock of equal gain combining (EGC) as

X

=

3

sum

119887=1

(119901sim119894thUE

119887I

119901sim119894thUE119887II

119901sim119894thUE119887III

119901sim119894thUE119887IV)

119879

(13)

Figure 5 describes the architecture ofmultiplexing systemby polarized 3D beams where each generated beam isdedicated to a piece of UE In this case the data rate is threetimes higher than the 3D-BF diversity system Here we alsoconsider multiple users with each of them equipping threecolocated antenna branches and note that in these two pro-posed schemes the zero-forcing BF is assumed and appliedat transmitter Tx (ie the BS) Compared with diversity casethe proposedmultiplexing scheme is relatively simple that thereceived signal for a specific UE after EGC process can begiven as

R119901sim119894thUE

119887

=

3

sum

119887=1

(h119901sim119894thUE

119887

(WTx119901sim119894thUE

119887

⊙ S119901sim119894thUE

119887

) + n119901sim119894thUE

119887

)

(14)

32 Array Selection Scheme for PM-MIMOArray System Thesharp beam as illustrated in Figure 2(b) performs quite wellin terms of BF interferences mitigation However it is notefficient to assign all AEs of a MUX to form one beamespecially for cell-edge UEs Overall AEs in a MUX can bedivided into several groups to form beams for separate UEsand this part analyses the minimum number of AEs requiredto mitigate BF interferences

Let us have two simultaneous beams point two adjacentpieces of UEs as demonstrated in Figure 6 where 119871 gives thebeam coverage and 119863 and 119889 denote the distance from UE toBS and the distance between the adjacent UEs respectivelyTo make the analysis meaningful we assume that there is asufficient amount of UE deployed in a cell and therewith theUEs are close each other resulting in 119889

1asymp V

1and 119889

2asymp V

2

According to Figure 6 in the case of UE (UE-1 and UE-2)located at a 3 dB beam area that is a half power beam-width(HPBW) area the HPBW needs to be controlled at less than2119889

1to avoid BF interferences On the other hand when UEs

(UE-3 and UE-4) are located at a beam peak area the HPBWcan be set larger than 2119889

2 In addition to assuming that UE is

distributed in a square cell which can be treated as a city blockfor horizontal BF or a building for vertical BF we provideFigure 7 for calculating average 119863 and 119889 Suppose that UEsfollow a spatial Poisson process with an intensity of 120588 so thenumber of UEs in a cell is given as

119870 = 1205881198712

(15)

The average distance between the BS and UE is calculated by

119863 = ∬1198712

1

1198712

119903 119889119903 119889120579

=2

1198712

(int

120603

0

int

119886 cos 120579

0

1199032

119889119903 119889120579 + int

1205872

120603

int

2119886 sin 120579

0

1199032

119889119903 119889120579)

=120585119871

2

(16)

where 120585 = ln(2 + radic5)12 + radic5 minus 2 ln((radic5 minus 1)2)3 asymp 1187The average distance between two adjacent pieces of UEs isgiven as

119889 = ∬119860

1

119860119903119889119903 119889120579 = int

2120587

0

int

119903UE

0

1199032

1205871199032

UE119889119903 119889120579 =

2

3119903UE (17)

where 119860 denotes the local coverage area of UE with a radiusof 119903UE depending on 120588

Because 119863 is calculated close to 1198712 the HPBW lt 2119889

needs to be maintained to avoid BF interferences Accordingto Su and Chang [16] we have

HPBW asymp 2

1003816100381610038161003816100381610038161003816arcsin(1391

120576

120587119875+ sin 120579

0)

1003816100381610038161003816100381610038161003816lt

4

3119903UE (18)

where 120576 denotes the array spacing factor that is 120576 = 120582119904 with119904 and 120582 representing the array spacing and signal wavelengthrespectively 120579

0is the signal incidence angle shifted from

the bore-sight direction and the antenna bore-sight is theaxis vertical to the orientation of the array alignment Forexample if the radius of a userrsquos local area (119903UE) is 15meters atleast 8 AEs are required to avoid BF interferences when 120576 = 2

and 1205790= 1205874 Please note that the above analysis is derived

based on the isotropic array antenna system The requirednumber of AEs may decrease by using the dipole antennabecause it does not radiate in the longitudinal direction ofan antenna structure that maintains a higher radiation gaincompared with the isotropic antenna

As discussed in Su andChang [16] and Liu [22] the beam-width is increased significantly when the beam steers to anangle far off the bore-sight direction such as the case of 120579

0in

(18) reaching 90∘ In order to avoid beam-with extension wepropose a scheme to cope with the large off bore-sight angleby dynamically selecting the set of polarized branches for 3D-BF that can effectivelyworkwithout increasing the dimensionof the array system As depicted in Figure 8 let 120572

119896 120573

119896 and 120574

119896

denote the acute angles corresponding to the119883119884 and119885 axesof the 119896th incident signal we have

120572119896= arcsin

radic1198872

119896

+ 1198882

119896

119863119896

120573119896= arcsin

radic1198862

119896

+ 1198882

119896

119863119896

120574119896= arcsin

radic1198862

119896

+ 1198872

119896

119863119896

(19)

Mobile Information Systems 7

11Tx

w

21Tx

w

31Tx

w

12

Txw

22Tx

w

32

Txw

Yextension

X

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

B1

B2

B3

B1

B2

B3

B1

B2

B3

13

Txw

23Tx

w

33

Txw

A1B2A1B3

A2B3

A3B3

A1B1

A2B2

A2B1

A3B2

A3B1

Kth UE

GI removal and FFTqth MUX of

PM-MIMO

APminus2B3

APminus2B2

APminus2B1

APminus1B2

APminus1B1

APminus1B3

APB3

APB2

APB1

wTxP2

wTxP3

wTxP1

wTx(pminus2)2

wTx(pminus2)3

wTx(pminus2)1

wTx(pminus1)3

wTx(pminus1)2

wTx(pminus1)1

B3

B2

B1

B3

B2

B1

B3

B2

B1

1st UE

2nd UE

3rd UE

(K minus 1)th UE

(K minus 2)th UE

IFFT and GI

Figure 5 Multiplexing system architecture by polarized 3D beams

BS

HPBW

UE-3

UE-4UE-2

UE-1

1

2

L

d1

d2D4

D3

D1

D2

Figure 6 Two beams steer toward two adjacent pieces of UE

8 Mobile Information Systems

UE-2

UE-1D

L

dr

r

UE

120579

minusL2

L2

PM-MIMO

Vertical BF plane

Horizontal BF

120603plane

X

Y

Z

0

Figure 7 Illustration of a square cell used for calculating 119863 and 119889

x

z

y

ck

bk

ak

Dk

120574k

120573k120572k

kth incident signal

PM-MIMO

Figure 8 Selection on the set of branches for 3D-BF via incident signal

where 120572119896 120573

119896 and 120574

119896isin (0 1205872) In order to avoid beam-

width extension by considering the off bore-sight anglethe following criteria need to be carried out for 3D-BFapplications

(i) When 120572119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198613to form the beam for the 119896th incident signal

(ii) When 120573119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198612to form the beam for the 119896th incident signal

(iii) When 120574119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198611to form the beam for the 119896th incident signal

Let 1199101(119905) 119910

2(119905) 119910

119896(119905) denote the incident signal

sequences that come from random directions Figure 9 thenprovides the flowchart of the proposed AE selection schemefor the PM-MIMO system According to Figure 9 the pro-posed scheme at first detects the incident signal sequencesand determines the minimum number of AEs used for 3D-BF via the criterion provided by (18) And then the proposedscheme categorizes the incident signal sequences into threecategories according tomax(120572

119896 120573

119896 120574

119896) For each category the

proposed schemes prepare the set of branches used for 3D-BF via the criteria provided before If the 3D-BF application

is dedicated to the cell-edge users the diversity by usingpolarized 3D beams is employed to maintain the cell-edgeusersrsquo performances Otherwise multiplexing via polarized3D beams is suggested in order to increase overall systemthroughput

4 Blind Channel Estimation to Avoid PilotContamination in PM-MIMO Array System

Theoretically the M-MIMO system is proved to have manyattractive features in wireless communications Howeverthese features are obtained mainly based on the perfectchannel estimation Practically the BS does not have perfectchannel state information that limits the exploration of M-MIMO systems Moreover conventional channel estimationby using training sequences may not be applicable to M-MIMO systems because usually there are tens or hundreds ofantennae applied in M-MIMO systems Spectrum efficiencycould not only be decreased dramatically by reserving manypilots for channel estimation but pilot contamination alsolimits performance because the pilot positions in a resourceblock have to be reused due to massive antenna employment[23ndash26]

Mobile Information Systems 9

No No

No

Start

Detection of incident signalfrom K UEs y1(t) y2(t) yK(t)

For yk(t) find max(120572k 120573k 120574k)

If 120572k is maximum If 120573k is maximum

YesYes

If yA119901B119887k

(t) belongs to cell-edge UE

Select AEs for yA119901B119887k

(t) and explore

diversity gain by STBC with 3D-BF

Select AEs for yA119901B119887k

(t) and explore

multiplexing gain by 3D-BF

k = k + 1

If k gt K

If k gt K

Yes

End

No

Categorize yk(t) to yA119901B3k

(t) max(120572k 120573k 120574k) = 120572k

Categorize yk(t) to yA119901B1k

(t) max(120572k 120573k 120574k) = 120574k

Categorize yk(t) to yA119901B2k

(t) max(120572k 120573k 120574k) = 120573k

Yes

Yes

No

Figure 9 Flowchart of the proposed AE selection scheme for PM-MIMO system

The BCE approach which requires no or a minimalnumber of pilots needs to be applied in M-MIMO systemsOne of the BCE strategies is based on eigenvalue decompo-sition (EVD) for the covariance matrix of a received signalthat needs to preserve pairwise orthogonality among channelvectors [27ndash29] Let us define an M-MIMO system model as

y119896= Hx

119896+ n

119896 (20)

where x119896is the transmitted symbolsH is an119872-by-119873 channel

matrix between the BS and the 119896th UE and n119896denotes

the additive white noise The covariance matrix of thereceived signal is then defined by

Ry119896

≜ y119896y119867119896

= HRx119896

H119867

+ Rn119896

(21)

where 119867 represents the Hermitian Transpose operationAdditionally multiplyingH at both sides of (21) we have

Ry119896

H = HRx119896

H119867H +H (22)

10 Mobile Information Systems

From the law of large number the channel vectors betweenthe BS and the deployed UEs become very long random andpairwise orthogonal which satisfies the condition

1

119872H119867H 997888rarr I

119873 as 119872 997888rarr infin (23)

Thereafter the estimated channel can be obtained as theeigenvectors of Ry

119896

via EVD processing [29]Note that since we focus on the link-level performance

the element of channel matrix H should be normalized andonly the additive noise and fast fading effects are taken intoconsideration to generate H If the array spacing is largerthan a half wave-length the elements of H would be lowlycorrelated and then the condition of (23) is easy to be satisfiedas reported elsewhere [30] where the BS AEs are usually sep-arated by several wave-lengths resulting in an uncorrelatedTx radiation pattern to preserve the pairwise orthogonalityamong channel vectors However in space-limitedM-MIMOsystems the pairwise orthogonality cannot be maintainedbecause the adjacent AE space is fixed normally at equal

or less than a half signal wave-length Consequently in thispaper we modify the EVD-based blind channel estimationscheme studied in Ngo and Larsson [29] The modifiedBCE approach can exploit the pairwise orthogonality via theparticular characteristics of PM-MIMO systems that is thepolarized cross-branch links in the system usually are uncor-related even though the adjacent AE spacing is set equal toor less than a half signal wave-length [17]

Based on other researches [14 16 31] an extension of thechannel matrix for PM-MIMO systems can be represented as

HPM-MIMO (119905)

= (

hTx1198601minusRx119860

1(119905) sdot sdot sdot hTx119860

1minusRx119860

(119905)

d

hTx119860119875minusRx119860

1(119905) sdot sdot sdot hTx119860

119875minusRx119860

(119905)

)

(24)

where

hTx119860119901minusRx119860

(119905) = radic

120578

119868

119868

sum

119894=1

(

ℎTx1198601199011198611minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198611(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198612(119905) ℎTx119860

1199011198612minusRx119860

1198612(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198612(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198613(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198613(119905) ℎTx119860

1199011198613minusRx119860

1198613(119905)

) (25)

Here 120578 and 119868 denote the transmit power and the numberof scatterers respectively Channel matrix (24) has a size of3119875-by-3 which is composed of 3-by-3 submatrices Eachsubmatrix holds the polarized cross-branch links between the119875th AE of Tx (the BS) and the th AE (UE) of receiver (Rx)Please note that throughout the paper theUE is assumedwithone AE that is = 1 The channel vectors of submatrix(25) are random and pairwise orthogonal because the polar-ized links from a Tx AE with three orthogonal branches toa single Rx branch are usually highly orthogonal [17] Con-sequently we can apply the EVD-based BCE via submatrixof (25) By redefining the covariance matrix of the receivedsignal as

Ry119896

≜ y119896y119867119896

= hTx119860119901minusRx119860

Rx119896

h119867Tx119860119901minusRx119860

+ Rn119896

(26)

the estimated channel can be obtained as the eigenvec-tors of Ry

119896

via EVD processing because the condition of(13)h119867Tx119860

119901minusRx119860

hTx119860119901minusRx119860

rarr I3is satisfied

5 Performance Verification

Table 1 lists the parameters settings of the performance veri-fication based on the LTE-A specification [32] The downlinkdata mapping for LTE-A resource blocks used in simulationsis demonstrated in Figure 10 which is based on theQO-STBC

symbol matrix of (5)We use the training sequences providedby [32] which are defined as

119903119897119899119904(119898) =

1

radic2(1 minus 2 sdot 119888 (2119898))

+ 1198951

radic2(1 minus 2 sdot 119888 (2119898 + 1))

(27)

where 119898 = 0 1 2119873max119863119871

119877119861

minus 1 The pilot density is 143and the initialization of 119888 is defined as

119888init = 210

sdot (7 sdot (119899119904+ 1) + 119897 + 1) sdot (2 sdot 119873

cellID + 1) + 2

sdot 119873cellID + 119873CP

(28)

where 119899119904is the slot number within a frame and

119873CP =

1 for normal CP

0 for extended CP(29)

Figure 11 depicts the probability densities of the HPBWgenerated in simulations where the HPBW can be effectivelykept as 50∘ on average by using the proposed AE selectionscheme of Figure 9 However the average HPBW extends byabout 15∘ when not considering the off bore-sight angle effectThis demonstrates that the proposed AE selection scheme isrobust that can optimize the generated beamwidth to avoidBF interference

Mobile Information Systems 11

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Branch A1B1 Branch A2B1

(a) Data mapping at Tx1198601199011198611

minus

minus

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1110

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Figure 10 Downlink data mapping of the LTE-A resource blocks used in the simulation

12 Mobile Information Systems

90

0005

001

0015

002

0025

003

With the proposed AE selection schemeWithout the proposed AE selection scheme

30 40 50 60 70 800

HPBW (deg)

Figure 11 Probability density of HPBW

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300

Case 2 PACE outdoor LOS 3kmhCase 3 PACE outdoor LOS 3kmh

Case 1 PACE outdoor LOS 3kmhCase 3 PACE outdoor NLOS 3kmhCase 2 PACE outdoor NLOS 3kmhCase 1 PACE outdoor NLOS 3kmh

EbN0 (dB)

Figure 12Users average BLERperformances based on the proposeddiversity system architecture

Figure 12 compares the usersrsquo average block error rate(BLER) performances obtained based on the proposeddiversity system architecture by using different transmissionschemes including Case 1 without STBC and TxBF Case2 with STBC only and Case 3 with STBC and TxBF viathe LTE pilot-assistant practical channel estimation (PACE)approach According to Figure 12 Case 1 has the worstperformance because there is no space-time coding and BFgain achieved About 17 dB of signal-to-noise ratio (SNR)gain at the target BLER can be achieved by Case 2 comparedwith Case 1 under the non-line-of-sight NLOS scenarioThere is about a 1 dB SNR gain that can be further achievedby employing the TxBF of Case 3 In addition the simulationresults under the LOS scenario are also provided as acomparison where almost 7 dB gain can be obtained whenthe LOS exists for those three cases

Next we simulate the BCE approaches and compare itsefficiency with the PACE based on the proposed diversitysystemarchitecture Figure 13 demonstrates the usersrsquo averageBLER via PACE and BCE approaches for three different

Table 1 Simulation parameters

Parameters ValueCarrier frequency 18GHzSystem bandwidth 20MHzFFT size 2048Number of data carriers 1200Number of samples in CP 144Subcarrier spacing 15 kHzBS antenna configuration(PM-MIMO) 1 MUX times 32 AE times 3 branches

BS AE spacing Half wavelengthUserrsquos antenna configuration 1 AE times 3 branches

Number of users 4 for 3D-BF diversity12 for 3D-BF multiplexing

Radius of userrsquos local area (119903UE) 15mAntenna type DipoleModulation QPSK

Number of scatterersOutdoor 4 clusters with 16scatterers per cluster (64 in

total)Scattering sphere radius 10mVelocity of UEs 3 60 and 120 kmhFading Flat

XPD value 58 dB and 97 dB for NLOSand LOS

Correlation 032 and 034 for NLOS andLOS

Rician 119870-factor 9 dB

userrsquos velocities including 3 60 and 120 kmh under theNLOS scenario An extension of other researches [14 31] isapplied to simulations of the polarized MIMO channel forwhich channel characteristics are also listed in Table 1 Wesee that the PACE performance decreases a lot due to highmobility at 60 and 120 kmh which indicates that the numberof pilots is not enough to compensate the channel correctlyin an environment with fast time-varying phase responseThe pilot density is 143 for PACE scheme and by consid-ering the trade-off regarding spectrum efficiency BCE thatrequires no or a minimal number of pilots might be betteremployed Figure 13 additionally shows the performances ofBCE schemes where performance is found that is not relevantto the userrsquos velocity Compared with the BCE reported byNgo and Larsson [29] our proposed BCE performance isbetter because the EVD is based on low correlated submatrixand has less complexity for doing the EVD based on asubmatrix with a smaller size Due to no pilot contaminationby BCE approach the proposed BCE outperforms PACEfor a velocity of 3 kmh when 119864

119887119873

0is less than 25 dB

However BCE has a higher complexity than PACE and itis condition constraint Again according to Figure 13 BCEperforms worse than PACE with a velocity of 3 kmh when119864119887119873

0is larger than 25 dB and the trend of error floor for

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

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LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia

International Journal of

Biomedical Imaging

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

6 Mobile Information Systems

where Τ119901sim119902119887

is defined as

Τ119901sim119894thUE

119887

= (119901sim119894thUE

119887I

lowast

119901sim119894thUE119887II

119901sim119894thUE119887III

lowast

119901sim119894thUE119887IV)

119879

(12)

by taking the conjugate of the second and the fourth elementsof R

119901sim119894thUE119887

The final output is obtained by the functionalblock of equal gain combining (EGC) as

X

=

3

sum

119887=1

(119901sim119894thUE

119887I

119901sim119894thUE119887II

119901sim119894thUE119887III

119901sim119894thUE119887IV)

119879

(13)

Figure 5 describes the architecture ofmultiplexing systemby polarized 3D beams where each generated beam isdedicated to a piece of UE In this case the data rate is threetimes higher than the 3D-BF diversity system Here we alsoconsider multiple users with each of them equipping threecolocated antenna branches and note that in these two pro-posed schemes the zero-forcing BF is assumed and appliedat transmitter Tx (ie the BS) Compared with diversity casethe proposedmultiplexing scheme is relatively simple that thereceived signal for a specific UE after EGC process can begiven as

R119901sim119894thUE

119887

=

3

sum

119887=1

(h119901sim119894thUE

119887

(WTx119901sim119894thUE

119887

⊙ S119901sim119894thUE

119887

) + n119901sim119894thUE

119887

)

(14)

32 Array Selection Scheme for PM-MIMOArray System Thesharp beam as illustrated in Figure 2(b) performs quite wellin terms of BF interferences mitigation However it is notefficient to assign all AEs of a MUX to form one beamespecially for cell-edge UEs Overall AEs in a MUX can bedivided into several groups to form beams for separate UEsand this part analyses the minimum number of AEs requiredto mitigate BF interferences

Let us have two simultaneous beams point two adjacentpieces of UEs as demonstrated in Figure 6 where 119871 gives thebeam coverage and 119863 and 119889 denote the distance from UE toBS and the distance between the adjacent UEs respectivelyTo make the analysis meaningful we assume that there is asufficient amount of UE deployed in a cell and therewith theUEs are close each other resulting in 119889

1asymp V

1and 119889

2asymp V

2

According to Figure 6 in the case of UE (UE-1 and UE-2)located at a 3 dB beam area that is a half power beam-width(HPBW) area the HPBW needs to be controlled at less than2119889

1to avoid BF interferences On the other hand when UEs

(UE-3 and UE-4) are located at a beam peak area the HPBWcan be set larger than 2119889

2 In addition to assuming that UE is

distributed in a square cell which can be treated as a city blockfor horizontal BF or a building for vertical BF we provideFigure 7 for calculating average 119863 and 119889 Suppose that UEsfollow a spatial Poisson process with an intensity of 120588 so thenumber of UEs in a cell is given as

119870 = 1205881198712

(15)

The average distance between the BS and UE is calculated by

119863 = ∬1198712

1

1198712

119903 119889119903 119889120579

=2

1198712

(int

120603

0

int

119886 cos 120579

0

1199032

119889119903 119889120579 + int

1205872

120603

int

2119886 sin 120579

0

1199032

119889119903 119889120579)

=120585119871

2

(16)

where 120585 = ln(2 + radic5)12 + radic5 minus 2 ln((radic5 minus 1)2)3 asymp 1187The average distance between two adjacent pieces of UEs isgiven as

119889 = ∬119860

1

119860119903119889119903 119889120579 = int

2120587

0

int

119903UE

0

1199032

1205871199032

UE119889119903 119889120579 =

2

3119903UE (17)

where 119860 denotes the local coverage area of UE with a radiusof 119903UE depending on 120588

Because 119863 is calculated close to 1198712 the HPBW lt 2119889

needs to be maintained to avoid BF interferences Accordingto Su and Chang [16] we have

HPBW asymp 2

1003816100381610038161003816100381610038161003816arcsin(1391

120576

120587119875+ sin 120579

0)

1003816100381610038161003816100381610038161003816lt

4

3119903UE (18)

where 120576 denotes the array spacing factor that is 120576 = 120582119904 with119904 and 120582 representing the array spacing and signal wavelengthrespectively 120579

0is the signal incidence angle shifted from

the bore-sight direction and the antenna bore-sight is theaxis vertical to the orientation of the array alignment Forexample if the radius of a userrsquos local area (119903UE) is 15meters atleast 8 AEs are required to avoid BF interferences when 120576 = 2

and 1205790= 1205874 Please note that the above analysis is derived

based on the isotropic array antenna system The requirednumber of AEs may decrease by using the dipole antennabecause it does not radiate in the longitudinal direction ofan antenna structure that maintains a higher radiation gaincompared with the isotropic antenna

As discussed in Su andChang [16] and Liu [22] the beam-width is increased significantly when the beam steers to anangle far off the bore-sight direction such as the case of 120579

0in

(18) reaching 90∘ In order to avoid beam-with extension wepropose a scheme to cope with the large off bore-sight angleby dynamically selecting the set of polarized branches for 3D-BF that can effectivelyworkwithout increasing the dimensionof the array system As depicted in Figure 8 let 120572

119896 120573

119896 and 120574

119896

denote the acute angles corresponding to the119883119884 and119885 axesof the 119896th incident signal we have

120572119896= arcsin

radic1198872

119896

+ 1198882

119896

119863119896

120573119896= arcsin

radic1198862

119896

+ 1198882

119896

119863119896

120574119896= arcsin

radic1198862

119896

+ 1198872

119896

119863119896

(19)

Mobile Information Systems 7

11Tx

w

21Tx

w

31Tx

w

12

Txw

22Tx

w

32

Txw

Yextension

X

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

B1

B2

B3

B1

B2

B3

B1

B2

B3

13

Txw

23Tx

w

33

Txw

A1B2A1B3

A2B3

A3B3

A1B1

A2B2

A2B1

A3B2

A3B1

Kth UE

GI removal and FFTqth MUX of

PM-MIMO

APminus2B3

APminus2B2

APminus2B1

APminus1B2

APminus1B1

APminus1B3

APB3

APB2

APB1

wTxP2

wTxP3

wTxP1

wTx(pminus2)2

wTx(pminus2)3

wTx(pminus2)1

wTx(pminus1)3

wTx(pminus1)2

wTx(pminus1)1

B3

B2

B1

B3

B2

B1

B3

B2

B1

1st UE

2nd UE

3rd UE

(K minus 1)th UE

(K minus 2)th UE

IFFT and GI

Figure 5 Multiplexing system architecture by polarized 3D beams

BS

HPBW

UE-3

UE-4UE-2

UE-1

1

2

L

d1

d2D4

D3

D1

D2

Figure 6 Two beams steer toward two adjacent pieces of UE

8 Mobile Information Systems

UE-2

UE-1D

L

dr

r

UE

120579

minusL2

L2

PM-MIMO

Vertical BF plane

Horizontal BF

120603plane

X

Y

Z

0

Figure 7 Illustration of a square cell used for calculating 119863 and 119889

x

z

y

ck

bk

ak

Dk

120574k

120573k120572k

kth incident signal

PM-MIMO

Figure 8 Selection on the set of branches for 3D-BF via incident signal

where 120572119896 120573

119896 and 120574

119896isin (0 1205872) In order to avoid beam-

width extension by considering the off bore-sight anglethe following criteria need to be carried out for 3D-BFapplications

(i) When 120572119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198613to form the beam for the 119896th incident signal

(ii) When 120573119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198612to form the beam for the 119896th incident signal

(iii) When 120574119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198611to form the beam for the 119896th incident signal

Let 1199101(119905) 119910

2(119905) 119910

119896(119905) denote the incident signal

sequences that come from random directions Figure 9 thenprovides the flowchart of the proposed AE selection schemefor the PM-MIMO system According to Figure 9 the pro-posed scheme at first detects the incident signal sequencesand determines the minimum number of AEs used for 3D-BF via the criterion provided by (18) And then the proposedscheme categorizes the incident signal sequences into threecategories according tomax(120572

119896 120573

119896 120574

119896) For each category the

proposed schemes prepare the set of branches used for 3D-BF via the criteria provided before If the 3D-BF application

is dedicated to the cell-edge users the diversity by usingpolarized 3D beams is employed to maintain the cell-edgeusersrsquo performances Otherwise multiplexing via polarized3D beams is suggested in order to increase overall systemthroughput

4 Blind Channel Estimation to Avoid PilotContamination in PM-MIMO Array System

Theoretically the M-MIMO system is proved to have manyattractive features in wireless communications Howeverthese features are obtained mainly based on the perfectchannel estimation Practically the BS does not have perfectchannel state information that limits the exploration of M-MIMO systems Moreover conventional channel estimationby using training sequences may not be applicable to M-MIMO systems because usually there are tens or hundreds ofantennae applied in M-MIMO systems Spectrum efficiencycould not only be decreased dramatically by reserving manypilots for channel estimation but pilot contamination alsolimits performance because the pilot positions in a resourceblock have to be reused due to massive antenna employment[23ndash26]

Mobile Information Systems 9

No No

No

Start

Detection of incident signalfrom K UEs y1(t) y2(t) yK(t)

For yk(t) find max(120572k 120573k 120574k)

If 120572k is maximum If 120573k is maximum

YesYes

If yA119901B119887k

(t) belongs to cell-edge UE

Select AEs for yA119901B119887k

(t) and explore

diversity gain by STBC with 3D-BF

Select AEs for yA119901B119887k

(t) and explore

multiplexing gain by 3D-BF

k = k + 1

If k gt K

If k gt K

Yes

End

No

Categorize yk(t) to yA119901B3k

(t) max(120572k 120573k 120574k) = 120572k

Categorize yk(t) to yA119901B1k

(t) max(120572k 120573k 120574k) = 120574k

Categorize yk(t) to yA119901B2k

(t) max(120572k 120573k 120574k) = 120573k

Yes

Yes

No

Figure 9 Flowchart of the proposed AE selection scheme for PM-MIMO system

The BCE approach which requires no or a minimalnumber of pilots needs to be applied in M-MIMO systemsOne of the BCE strategies is based on eigenvalue decompo-sition (EVD) for the covariance matrix of a received signalthat needs to preserve pairwise orthogonality among channelvectors [27ndash29] Let us define an M-MIMO system model as

y119896= Hx

119896+ n

119896 (20)

where x119896is the transmitted symbolsH is an119872-by-119873 channel

matrix between the BS and the 119896th UE and n119896denotes

the additive white noise The covariance matrix of thereceived signal is then defined by

Ry119896

≜ y119896y119867119896

= HRx119896

H119867

+ Rn119896

(21)

where 119867 represents the Hermitian Transpose operationAdditionally multiplyingH at both sides of (21) we have

Ry119896

H = HRx119896

H119867H +H (22)

10 Mobile Information Systems

From the law of large number the channel vectors betweenthe BS and the deployed UEs become very long random andpairwise orthogonal which satisfies the condition

1

119872H119867H 997888rarr I

119873 as 119872 997888rarr infin (23)

Thereafter the estimated channel can be obtained as theeigenvectors of Ry

119896

via EVD processing [29]Note that since we focus on the link-level performance

the element of channel matrix H should be normalized andonly the additive noise and fast fading effects are taken intoconsideration to generate H If the array spacing is largerthan a half wave-length the elements of H would be lowlycorrelated and then the condition of (23) is easy to be satisfiedas reported elsewhere [30] where the BS AEs are usually sep-arated by several wave-lengths resulting in an uncorrelatedTx radiation pattern to preserve the pairwise orthogonalityamong channel vectors However in space-limitedM-MIMOsystems the pairwise orthogonality cannot be maintainedbecause the adjacent AE space is fixed normally at equal

or less than a half signal wave-length Consequently in thispaper we modify the EVD-based blind channel estimationscheme studied in Ngo and Larsson [29] The modifiedBCE approach can exploit the pairwise orthogonality via theparticular characteristics of PM-MIMO systems that is thepolarized cross-branch links in the system usually are uncor-related even though the adjacent AE spacing is set equal toor less than a half signal wave-length [17]

Based on other researches [14 16 31] an extension of thechannel matrix for PM-MIMO systems can be represented as

HPM-MIMO (119905)

= (

hTx1198601minusRx119860

1(119905) sdot sdot sdot hTx119860

1minusRx119860

(119905)

d

hTx119860119875minusRx119860

1(119905) sdot sdot sdot hTx119860

119875minusRx119860

(119905)

)

(24)

where

hTx119860119901minusRx119860

(119905) = radic

120578

119868

119868

sum

119894=1

(

ℎTx1198601199011198611minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198611(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198612(119905) ℎTx119860

1199011198612minusRx119860

1198612(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198612(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198613(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198613(119905) ℎTx119860

1199011198613minusRx119860

1198613(119905)

) (25)

Here 120578 and 119868 denote the transmit power and the numberof scatterers respectively Channel matrix (24) has a size of3119875-by-3 which is composed of 3-by-3 submatrices Eachsubmatrix holds the polarized cross-branch links between the119875th AE of Tx (the BS) and the th AE (UE) of receiver (Rx)Please note that throughout the paper theUE is assumedwithone AE that is = 1 The channel vectors of submatrix(25) are random and pairwise orthogonal because the polar-ized links from a Tx AE with three orthogonal branches toa single Rx branch are usually highly orthogonal [17] Con-sequently we can apply the EVD-based BCE via submatrixof (25) By redefining the covariance matrix of the receivedsignal as

Ry119896

≜ y119896y119867119896

= hTx119860119901minusRx119860

Rx119896

h119867Tx119860119901minusRx119860

+ Rn119896

(26)

the estimated channel can be obtained as the eigenvec-tors of Ry

119896

via EVD processing because the condition of(13)h119867Tx119860

119901minusRx119860

hTx119860119901minusRx119860

rarr I3is satisfied

5 Performance Verification

Table 1 lists the parameters settings of the performance veri-fication based on the LTE-A specification [32] The downlinkdata mapping for LTE-A resource blocks used in simulationsis demonstrated in Figure 10 which is based on theQO-STBC

symbol matrix of (5)We use the training sequences providedby [32] which are defined as

119903119897119899119904(119898) =

1

radic2(1 minus 2 sdot 119888 (2119898))

+ 1198951

radic2(1 minus 2 sdot 119888 (2119898 + 1))

(27)

where 119898 = 0 1 2119873max119863119871

119877119861

minus 1 The pilot density is 143and the initialization of 119888 is defined as

119888init = 210

sdot (7 sdot (119899119904+ 1) + 119897 + 1) sdot (2 sdot 119873

cellID + 1) + 2

sdot 119873cellID + 119873CP

(28)

where 119899119904is the slot number within a frame and

119873CP =

1 for normal CP

0 for extended CP(29)

Figure 11 depicts the probability densities of the HPBWgenerated in simulations where the HPBW can be effectivelykept as 50∘ on average by using the proposed AE selectionscheme of Figure 9 However the average HPBW extends byabout 15∘ when not considering the off bore-sight angle effectThis demonstrates that the proposed AE selection scheme isrobust that can optimize the generated beamwidth to avoidBF interference

Mobile Information Systems 11

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Figure 10 Downlink data mapping of the LTE-A resource blocks used in the simulation

12 Mobile Information Systems

90

0005

001

0015

002

0025

003

With the proposed AE selection schemeWithout the proposed AE selection scheme

30 40 50 60 70 800

HPBW (deg)

Figure 11 Probability density of HPBW

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300

Case 2 PACE outdoor LOS 3kmhCase 3 PACE outdoor LOS 3kmh

Case 1 PACE outdoor LOS 3kmhCase 3 PACE outdoor NLOS 3kmhCase 2 PACE outdoor NLOS 3kmhCase 1 PACE outdoor NLOS 3kmh

EbN0 (dB)

Figure 12Users average BLERperformances based on the proposeddiversity system architecture

Figure 12 compares the usersrsquo average block error rate(BLER) performances obtained based on the proposeddiversity system architecture by using different transmissionschemes including Case 1 without STBC and TxBF Case2 with STBC only and Case 3 with STBC and TxBF viathe LTE pilot-assistant practical channel estimation (PACE)approach According to Figure 12 Case 1 has the worstperformance because there is no space-time coding and BFgain achieved About 17 dB of signal-to-noise ratio (SNR)gain at the target BLER can be achieved by Case 2 comparedwith Case 1 under the non-line-of-sight NLOS scenarioThere is about a 1 dB SNR gain that can be further achievedby employing the TxBF of Case 3 In addition the simulationresults under the LOS scenario are also provided as acomparison where almost 7 dB gain can be obtained whenthe LOS exists for those three cases

Next we simulate the BCE approaches and compare itsefficiency with the PACE based on the proposed diversitysystemarchitecture Figure 13 demonstrates the usersrsquo averageBLER via PACE and BCE approaches for three different

Table 1 Simulation parameters

Parameters ValueCarrier frequency 18GHzSystem bandwidth 20MHzFFT size 2048Number of data carriers 1200Number of samples in CP 144Subcarrier spacing 15 kHzBS antenna configuration(PM-MIMO) 1 MUX times 32 AE times 3 branches

BS AE spacing Half wavelengthUserrsquos antenna configuration 1 AE times 3 branches

Number of users 4 for 3D-BF diversity12 for 3D-BF multiplexing

Radius of userrsquos local area (119903UE) 15mAntenna type DipoleModulation QPSK

Number of scatterersOutdoor 4 clusters with 16scatterers per cluster (64 in

total)Scattering sphere radius 10mVelocity of UEs 3 60 and 120 kmhFading Flat

XPD value 58 dB and 97 dB for NLOSand LOS

Correlation 032 and 034 for NLOS andLOS

Rician 119870-factor 9 dB

userrsquos velocities including 3 60 and 120 kmh under theNLOS scenario An extension of other researches [14 31] isapplied to simulations of the polarized MIMO channel forwhich channel characteristics are also listed in Table 1 Wesee that the PACE performance decreases a lot due to highmobility at 60 and 120 kmh which indicates that the numberof pilots is not enough to compensate the channel correctlyin an environment with fast time-varying phase responseThe pilot density is 143 for PACE scheme and by consid-ering the trade-off regarding spectrum efficiency BCE thatrequires no or a minimal number of pilots might be betteremployed Figure 13 additionally shows the performances ofBCE schemes where performance is found that is not relevantto the userrsquos velocity Compared with the BCE reported byNgo and Larsson [29] our proposed BCE performance isbetter because the EVD is based on low correlated submatrixand has less complexity for doing the EVD based on asubmatrix with a smaller size Due to no pilot contaminationby BCE approach the proposed BCE outperforms PACEfor a velocity of 3 kmh when 119864

119887119873

0is less than 25 dB

However BCE has a higher complexity than PACE and itis condition constraint Again according to Figure 13 BCEperforms worse than PACE with a velocity of 3 kmh when119864119887119873

0is larger than 25 dB and the trend of error floor for

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

10minus1

100

UEs

aver

age B

LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia

International Journal of

Biomedical Imaging

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mobile Information Systems 7

11Tx

w

21Tx

w

31Tx

w

12

Txw

22Tx

w

32

Txw

Yextension

X

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

Rx combining

B1

B2

B3

B1

B2

B3

B1

B2

B3

13

Txw

23Tx

w

33

Txw

A1B2A1B3

A2B3

A3B3

A1B1

A2B2

A2B1

A3B2

A3B1

Kth UE

GI removal and FFTqth MUX of

PM-MIMO

APminus2B3

APminus2B2

APminus2B1

APminus1B2

APminus1B1

APminus1B3

APB3

APB2

APB1

wTxP2

wTxP3

wTxP1

wTx(pminus2)2

wTx(pminus2)3

wTx(pminus2)1

wTx(pminus1)3

wTx(pminus1)2

wTx(pminus1)1

B3

B2

B1

B3

B2

B1

B3

B2

B1

1st UE

2nd UE

3rd UE

(K minus 1)th UE

(K minus 2)th UE

IFFT and GI

Figure 5 Multiplexing system architecture by polarized 3D beams

BS

HPBW

UE-3

UE-4UE-2

UE-1

1

2

L

d1

d2D4

D3

D1

D2

Figure 6 Two beams steer toward two adjacent pieces of UE

8 Mobile Information Systems

UE-2

UE-1D

L

dr

r

UE

120579

minusL2

L2

PM-MIMO

Vertical BF plane

Horizontal BF

120603plane

X

Y

Z

0

Figure 7 Illustration of a square cell used for calculating 119863 and 119889

x

z

y

ck

bk

ak

Dk

120574k

120573k120572k

kth incident signal

PM-MIMO

Figure 8 Selection on the set of branches for 3D-BF via incident signal

where 120572119896 120573

119896 and 120574

119896isin (0 1205872) In order to avoid beam-

width extension by considering the off bore-sight anglethe following criteria need to be carried out for 3D-BFapplications

(i) When 120572119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198613to form the beam for the 119896th incident signal

(ii) When 120573119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198612to form the beam for the 119896th incident signal

(iii) When 120574119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198611to form the beam for the 119896th incident signal

Let 1199101(119905) 119910

2(119905) 119910

119896(119905) denote the incident signal

sequences that come from random directions Figure 9 thenprovides the flowchart of the proposed AE selection schemefor the PM-MIMO system According to Figure 9 the pro-posed scheme at first detects the incident signal sequencesand determines the minimum number of AEs used for 3D-BF via the criterion provided by (18) And then the proposedscheme categorizes the incident signal sequences into threecategories according tomax(120572

119896 120573

119896 120574

119896) For each category the

proposed schemes prepare the set of branches used for 3D-BF via the criteria provided before If the 3D-BF application

is dedicated to the cell-edge users the diversity by usingpolarized 3D beams is employed to maintain the cell-edgeusersrsquo performances Otherwise multiplexing via polarized3D beams is suggested in order to increase overall systemthroughput

4 Blind Channel Estimation to Avoid PilotContamination in PM-MIMO Array System

Theoretically the M-MIMO system is proved to have manyattractive features in wireless communications Howeverthese features are obtained mainly based on the perfectchannel estimation Practically the BS does not have perfectchannel state information that limits the exploration of M-MIMO systems Moreover conventional channel estimationby using training sequences may not be applicable to M-MIMO systems because usually there are tens or hundreds ofantennae applied in M-MIMO systems Spectrum efficiencycould not only be decreased dramatically by reserving manypilots for channel estimation but pilot contamination alsolimits performance because the pilot positions in a resourceblock have to be reused due to massive antenna employment[23ndash26]

Mobile Information Systems 9

No No

No

Start

Detection of incident signalfrom K UEs y1(t) y2(t) yK(t)

For yk(t) find max(120572k 120573k 120574k)

If 120572k is maximum If 120573k is maximum

YesYes

If yA119901B119887k

(t) belongs to cell-edge UE

Select AEs for yA119901B119887k

(t) and explore

diversity gain by STBC with 3D-BF

Select AEs for yA119901B119887k

(t) and explore

multiplexing gain by 3D-BF

k = k + 1

If k gt K

If k gt K

Yes

End

No

Categorize yk(t) to yA119901B3k

(t) max(120572k 120573k 120574k) = 120572k

Categorize yk(t) to yA119901B1k

(t) max(120572k 120573k 120574k) = 120574k

Categorize yk(t) to yA119901B2k

(t) max(120572k 120573k 120574k) = 120573k

Yes

Yes

No

Figure 9 Flowchart of the proposed AE selection scheme for PM-MIMO system

The BCE approach which requires no or a minimalnumber of pilots needs to be applied in M-MIMO systemsOne of the BCE strategies is based on eigenvalue decompo-sition (EVD) for the covariance matrix of a received signalthat needs to preserve pairwise orthogonality among channelvectors [27ndash29] Let us define an M-MIMO system model as

y119896= Hx

119896+ n

119896 (20)

where x119896is the transmitted symbolsH is an119872-by-119873 channel

matrix between the BS and the 119896th UE and n119896denotes

the additive white noise The covariance matrix of thereceived signal is then defined by

Ry119896

≜ y119896y119867119896

= HRx119896

H119867

+ Rn119896

(21)

where 119867 represents the Hermitian Transpose operationAdditionally multiplyingH at both sides of (21) we have

Ry119896

H = HRx119896

H119867H +H (22)

10 Mobile Information Systems

From the law of large number the channel vectors betweenthe BS and the deployed UEs become very long random andpairwise orthogonal which satisfies the condition

1

119872H119867H 997888rarr I

119873 as 119872 997888rarr infin (23)

Thereafter the estimated channel can be obtained as theeigenvectors of Ry

119896

via EVD processing [29]Note that since we focus on the link-level performance

the element of channel matrix H should be normalized andonly the additive noise and fast fading effects are taken intoconsideration to generate H If the array spacing is largerthan a half wave-length the elements of H would be lowlycorrelated and then the condition of (23) is easy to be satisfiedas reported elsewhere [30] where the BS AEs are usually sep-arated by several wave-lengths resulting in an uncorrelatedTx radiation pattern to preserve the pairwise orthogonalityamong channel vectors However in space-limitedM-MIMOsystems the pairwise orthogonality cannot be maintainedbecause the adjacent AE space is fixed normally at equal

or less than a half signal wave-length Consequently in thispaper we modify the EVD-based blind channel estimationscheme studied in Ngo and Larsson [29] The modifiedBCE approach can exploit the pairwise orthogonality via theparticular characteristics of PM-MIMO systems that is thepolarized cross-branch links in the system usually are uncor-related even though the adjacent AE spacing is set equal toor less than a half signal wave-length [17]

Based on other researches [14 16 31] an extension of thechannel matrix for PM-MIMO systems can be represented as

HPM-MIMO (119905)

= (

hTx1198601minusRx119860

1(119905) sdot sdot sdot hTx119860

1minusRx119860

(119905)

d

hTx119860119875minusRx119860

1(119905) sdot sdot sdot hTx119860

119875minusRx119860

(119905)

)

(24)

where

hTx119860119901minusRx119860

(119905) = radic

120578

119868

119868

sum

119894=1

(

ℎTx1198601199011198611minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198611(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198612(119905) ℎTx119860

1199011198612minusRx119860

1198612(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198612(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198613(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198613(119905) ℎTx119860

1199011198613minusRx119860

1198613(119905)

) (25)

Here 120578 and 119868 denote the transmit power and the numberof scatterers respectively Channel matrix (24) has a size of3119875-by-3 which is composed of 3-by-3 submatrices Eachsubmatrix holds the polarized cross-branch links between the119875th AE of Tx (the BS) and the th AE (UE) of receiver (Rx)Please note that throughout the paper theUE is assumedwithone AE that is = 1 The channel vectors of submatrix(25) are random and pairwise orthogonal because the polar-ized links from a Tx AE with three orthogonal branches toa single Rx branch are usually highly orthogonal [17] Con-sequently we can apply the EVD-based BCE via submatrixof (25) By redefining the covariance matrix of the receivedsignal as

Ry119896

≜ y119896y119867119896

= hTx119860119901minusRx119860

Rx119896

h119867Tx119860119901minusRx119860

+ Rn119896

(26)

the estimated channel can be obtained as the eigenvec-tors of Ry

119896

via EVD processing because the condition of(13)h119867Tx119860

119901minusRx119860

hTx119860119901minusRx119860

rarr I3is satisfied

5 Performance Verification

Table 1 lists the parameters settings of the performance veri-fication based on the LTE-A specification [32] The downlinkdata mapping for LTE-A resource blocks used in simulationsis demonstrated in Figure 10 which is based on theQO-STBC

symbol matrix of (5)We use the training sequences providedby [32] which are defined as

119903119897119899119904(119898) =

1

radic2(1 minus 2 sdot 119888 (2119898))

+ 1198951

radic2(1 minus 2 sdot 119888 (2119898 + 1))

(27)

where 119898 = 0 1 2119873max119863119871

119877119861

minus 1 The pilot density is 143and the initialization of 119888 is defined as

119888init = 210

sdot (7 sdot (119899119904+ 1) + 119897 + 1) sdot (2 sdot 119873

cellID + 1) + 2

sdot 119873cellID + 119873CP

(28)

where 119899119904is the slot number within a frame and

119873CP =

1 for normal CP

0 for extended CP(29)

Figure 11 depicts the probability densities of the HPBWgenerated in simulations where the HPBW can be effectivelykept as 50∘ on average by using the proposed AE selectionscheme of Figure 9 However the average HPBW extends byabout 15∘ when not considering the off bore-sight angle effectThis demonstrates that the proposed AE selection scheme isrobust that can optimize the generated beamwidth to avoidBF interference

Mobile Information Systems 11

PA2B1

PA2B1

PA2B1

PA2B1

0 1 3 4 5 6 7 8 9

0

1

9

8

7

6

5

4

3

2

Subframe

xlowast1

xlowast5

xlowast9

xlowast17

xlowast13

xlowast21

xlowast25

xlowast29

xlowast33

xlowast37

xlowast41

xlowast45

xlowast51

xlowast55

xlowast59

xlowast63

xlowast67

xlowast71

xlowast75

xlowast79

xlowast83

xlowast87

xlowast91

xlowast95

xlowast49

xlowast53

xlowast57

xlowast61

xlowast65

xlowast69

xlowast73

xlowast77

xlowast81

xlowast85

xlowast89

xlowast93

xlowast3

xlowast7

xlowast11

xlowast19

xlowast15

xlowast23

xlowast27

xlowast31

xlowast35

xlowast39

xlowast43

xlowast47

PA1B1

PA1B1

PA1B1

PA1B1

Reso

urce

blo

ck

13121111

10

10

x2

x6

x10

x14

x18

x22

x26

x30

x34

x38

x42

x46

x4

x8

x12

x16

x20

x24

x28

x32

x36

x40

x44

x48

x50

x54

x58

x62

x66

x70

x74

x78

x82

x86

x90

x94

x52

x56

x60

x64

x68

x72

x76

x80

x84

x88

x92

x96

x98

x102

x106

x110

x114

x118

x122

x126

x130

x134

x138

x142

x100

x104

x108

x112

x116

x120

x124

x128

x132

x136

x140

x144

xlowast99

xlowast103

xlowast107

xlowast111

xlowast115

xlowast119

xlowast123

xlowast127

xlowast131

xlowast135

xlowast139

xlowast143

xlowast97

xlowast101

xlowast105

xlowast109

xlowast113

xlowast117

xlowast121

xlowast125

xlowast129

xlowast133

xlowast137

xlowast14120 1 3 4 5 6 7 8 9

0

1

9

8

7

6

5

4

3

2

Subframe

xlowast1

xlowast5

xlowast9

xlowast17

xlowast13

xlowast21

xlowast25

xlowast29

xlowast33

xlowast37

xlowast41

xlowast45

xlowast51

xlowast55

xlowast59

xlowast63

xlowast67

xlowast71

xlowast75

xlowast79

xlowast83

xlowast87

xlowast91

xlowast95

xlowast49

xlowast53

xlowast57

xlowast61

xlowast65

xlowast69

xlowast73

xlowast77

xlowast81

xlowast85

xlowast89

xlowast93

xlowast3

xlowast7

xlowast11

xlowast19

xlowast15

xlowast23

xlowast27

xlowast31

xlowast35

xlowast39

xlowast43

xlowast47

Reso

urce

blo

ck

13121111

10

10

x2

x6

x10

x14

x18

x22

x26

x30

x34

x38

x42

x46

x4

x8

x12

x16

x20

x24

x28

x32

x36

x40

x44

x48

x50

x54

x58

x62

x66

x70

x74

x78

x82

x86

x90

x94

x52

x56

x60

x64

x68

x72

x76

x80

x84

x88

x92

x96

x98

x102

x106

x110

x114

x118

x122

x126

x130

x134

x138

x142

x100

x104

x108

x112

x116

x120

x124

x128

x132

x136

x140

x144

xlowast99

xlowast103

xlowast107

xlowast111

xlowast115

xlowast119

xlowast123

xlowast127

xlowast131

xlowast135

xlowast139

xlowast143

xlowast97

xlowast101

xlowast105

xlowast109

xlowast113

xlowast117

xlowast121

xlowast125

xlowast129

xlowast133

xlowast137

xlowast1412

Branch A1B1 Branch A2B1

(a) Data mapping at Tx1198601199011198611

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urce

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ck

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98765432

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PA1B2

PA1B2

PA1B2

PA1B2

1110

PA2B2

PA2B2

PA2B2

PA2B2

x3

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Reso

urce

blo

ck

01

98765432

xlowast4

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xlowast481110

20 1 3 4 5 6 7 8 9Subframe

131211131211 1020 1 3 4 5 6 7 8 9Subframe

10

x3

x7

x11

x15

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x27

x31

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x1

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x141

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xlowast132

xlowast136

xlowast140

xlowast144

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minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

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minus

minus

minus

minus

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minus

minus

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minus

x97

x101

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x141

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xlowast136

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xlowast144

Branch A1B2 Branch A2B2

(b) Data mapping at Tx1198601199011198612

xlowast49xlowast53

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Reso

urce

blo

ck

01

98765432

xlowast3

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xlowast47

PA1B3

PA1B3

PA1B3

PA1B3

1110

20 1 3 4 5 6 7 8 9Subframe

13121110

Branch A2B3

PA2B3PA2B3

PA2B3 PA2B3

x4

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xlowast141

xlowast99

xlowast103

xlowast107

xlowast111

xlowast115

xlowast119

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xlowast139

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xlowast49xlowast53

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xlowast51xlowast55

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xlowast71

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xlowast87

xlowast91

xlowast95

xlowast1

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xlowast9

xlowast17

xlowast13

xlowast21

xlowast25

xlowast29

xlowast33

xlowast37

xlowast41

xlowast45

Reso

urce

blo

ck

01

98765432

xlowast3

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xlowast15

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xlowast471110

20 1 3 4 5 6 7 8 9Subframe

13121110

x4

x8

x12

x16

x20

x24

x28

x32

x36

x40

x44

x48

x2

x6

x10

x14

x18

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x34

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x46

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x56

x60

x64

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x92

x96

x50

x54

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x66

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x74

x78

x82

x86

x90

x94

x100x104

x108

x112

x116

x120

x124

x128

x132

x136

x140

x144

x98

x102

x106

x110

x114

x118

x122

x126

x130

x134

x138

x142

xlowast97

xlowast101

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xlowast109

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xlowast129

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xlowast141

xlowast99

xlowast103

xlowast107

xlowast111

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xlowast119

xlowast123

xlowast127

xlowast131

xlowast135

xlowast139

xlowast143

Branch A1B3

(c) Data mapping at Tx1198601199011198613

Figure 10 Downlink data mapping of the LTE-A resource blocks used in the simulation

12 Mobile Information Systems

90

0005

001

0015

002

0025

003

With the proposed AE selection schemeWithout the proposed AE selection scheme

30 40 50 60 70 800

HPBW (deg)

Figure 11 Probability density of HPBW

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300

Case 2 PACE outdoor LOS 3kmhCase 3 PACE outdoor LOS 3kmh

Case 1 PACE outdoor LOS 3kmhCase 3 PACE outdoor NLOS 3kmhCase 2 PACE outdoor NLOS 3kmhCase 1 PACE outdoor NLOS 3kmh

EbN0 (dB)

Figure 12Users average BLERperformances based on the proposeddiversity system architecture

Figure 12 compares the usersrsquo average block error rate(BLER) performances obtained based on the proposeddiversity system architecture by using different transmissionschemes including Case 1 without STBC and TxBF Case2 with STBC only and Case 3 with STBC and TxBF viathe LTE pilot-assistant practical channel estimation (PACE)approach According to Figure 12 Case 1 has the worstperformance because there is no space-time coding and BFgain achieved About 17 dB of signal-to-noise ratio (SNR)gain at the target BLER can be achieved by Case 2 comparedwith Case 1 under the non-line-of-sight NLOS scenarioThere is about a 1 dB SNR gain that can be further achievedby employing the TxBF of Case 3 In addition the simulationresults under the LOS scenario are also provided as acomparison where almost 7 dB gain can be obtained whenthe LOS exists for those three cases

Next we simulate the BCE approaches and compare itsefficiency with the PACE based on the proposed diversitysystemarchitecture Figure 13 demonstrates the usersrsquo averageBLER via PACE and BCE approaches for three different

Table 1 Simulation parameters

Parameters ValueCarrier frequency 18GHzSystem bandwidth 20MHzFFT size 2048Number of data carriers 1200Number of samples in CP 144Subcarrier spacing 15 kHzBS antenna configuration(PM-MIMO) 1 MUX times 32 AE times 3 branches

BS AE spacing Half wavelengthUserrsquos antenna configuration 1 AE times 3 branches

Number of users 4 for 3D-BF diversity12 for 3D-BF multiplexing

Radius of userrsquos local area (119903UE) 15mAntenna type DipoleModulation QPSK

Number of scatterersOutdoor 4 clusters with 16scatterers per cluster (64 in

total)Scattering sphere radius 10mVelocity of UEs 3 60 and 120 kmhFading Flat

XPD value 58 dB and 97 dB for NLOSand LOS

Correlation 032 and 034 for NLOS andLOS

Rician 119870-factor 9 dB

userrsquos velocities including 3 60 and 120 kmh under theNLOS scenario An extension of other researches [14 31] isapplied to simulations of the polarized MIMO channel forwhich channel characteristics are also listed in Table 1 Wesee that the PACE performance decreases a lot due to highmobility at 60 and 120 kmh which indicates that the numberof pilots is not enough to compensate the channel correctlyin an environment with fast time-varying phase responseThe pilot density is 143 for PACE scheme and by consid-ering the trade-off regarding spectrum efficiency BCE thatrequires no or a minimal number of pilots might be betteremployed Figure 13 additionally shows the performances ofBCE schemes where performance is found that is not relevantto the userrsquos velocity Compared with the BCE reported byNgo and Larsson [29] our proposed BCE performance isbetter because the EVD is based on low correlated submatrixand has less complexity for doing the EVD based on asubmatrix with a smaller size Due to no pilot contaminationby BCE approach the proposed BCE outperforms PACEfor a velocity of 3 kmh when 119864

119887119873

0is less than 25 dB

However BCE has a higher complexity than PACE and itis condition constraint Again according to Figure 13 BCEperforms worse than PACE with a velocity of 3 kmh when119864119887119873

0is larger than 25 dB and the trend of error floor for

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

10minus1

100

UEs

aver

age B

LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

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8 Mobile Information Systems

UE-2

UE-1D

L

dr

r

UE

120579

minusL2

L2

PM-MIMO

Vertical BF plane

Horizontal BF

120603plane

X

Y

Z

0

Figure 7 Illustration of a square cell used for calculating 119863 and 119889

x

z

y

ck

bk

ak

Dk

120574k

120573k120572k

kth incident signal

PM-MIMO

Figure 8 Selection on the set of branches for 3D-BF via incident signal

where 120572119896 120573

119896 and 120574

119896isin (0 1205872) In order to avoid beam-

width extension by considering the off bore-sight anglethe following criteria need to be carried out for 3D-BFapplications

(i) When 120572119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198613to form the beam for the 119896th incident signal

(ii) When 120573119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198612to form the beam for the 119896th incident signal

(iii) When 120574119896= max(120572

119896 120573

119896 120574

119896) use the set of branches of

1198601199011198611to form the beam for the 119896th incident signal

Let 1199101(119905) 119910

2(119905) 119910

119896(119905) denote the incident signal

sequences that come from random directions Figure 9 thenprovides the flowchart of the proposed AE selection schemefor the PM-MIMO system According to Figure 9 the pro-posed scheme at first detects the incident signal sequencesand determines the minimum number of AEs used for 3D-BF via the criterion provided by (18) And then the proposedscheme categorizes the incident signal sequences into threecategories according tomax(120572

119896 120573

119896 120574

119896) For each category the

proposed schemes prepare the set of branches used for 3D-BF via the criteria provided before If the 3D-BF application

is dedicated to the cell-edge users the diversity by usingpolarized 3D beams is employed to maintain the cell-edgeusersrsquo performances Otherwise multiplexing via polarized3D beams is suggested in order to increase overall systemthroughput

4 Blind Channel Estimation to Avoid PilotContamination in PM-MIMO Array System

Theoretically the M-MIMO system is proved to have manyattractive features in wireless communications Howeverthese features are obtained mainly based on the perfectchannel estimation Practically the BS does not have perfectchannel state information that limits the exploration of M-MIMO systems Moreover conventional channel estimationby using training sequences may not be applicable to M-MIMO systems because usually there are tens or hundreds ofantennae applied in M-MIMO systems Spectrum efficiencycould not only be decreased dramatically by reserving manypilots for channel estimation but pilot contamination alsolimits performance because the pilot positions in a resourceblock have to be reused due to massive antenna employment[23ndash26]

Mobile Information Systems 9

No No

No

Start

Detection of incident signalfrom K UEs y1(t) y2(t) yK(t)

For yk(t) find max(120572k 120573k 120574k)

If 120572k is maximum If 120573k is maximum

YesYes

If yA119901B119887k

(t) belongs to cell-edge UE

Select AEs for yA119901B119887k

(t) and explore

diversity gain by STBC with 3D-BF

Select AEs for yA119901B119887k

(t) and explore

multiplexing gain by 3D-BF

k = k + 1

If k gt K

If k gt K

Yes

End

No

Categorize yk(t) to yA119901B3k

(t) max(120572k 120573k 120574k) = 120572k

Categorize yk(t) to yA119901B1k

(t) max(120572k 120573k 120574k) = 120574k

Categorize yk(t) to yA119901B2k

(t) max(120572k 120573k 120574k) = 120573k

Yes

Yes

No

Figure 9 Flowchart of the proposed AE selection scheme for PM-MIMO system

The BCE approach which requires no or a minimalnumber of pilots needs to be applied in M-MIMO systemsOne of the BCE strategies is based on eigenvalue decompo-sition (EVD) for the covariance matrix of a received signalthat needs to preserve pairwise orthogonality among channelvectors [27ndash29] Let us define an M-MIMO system model as

y119896= Hx

119896+ n

119896 (20)

where x119896is the transmitted symbolsH is an119872-by-119873 channel

matrix between the BS and the 119896th UE and n119896denotes

the additive white noise The covariance matrix of thereceived signal is then defined by

Ry119896

≜ y119896y119867119896

= HRx119896

H119867

+ Rn119896

(21)

where 119867 represents the Hermitian Transpose operationAdditionally multiplyingH at both sides of (21) we have

Ry119896

H = HRx119896

H119867H +H (22)

10 Mobile Information Systems

From the law of large number the channel vectors betweenthe BS and the deployed UEs become very long random andpairwise orthogonal which satisfies the condition

1

119872H119867H 997888rarr I

119873 as 119872 997888rarr infin (23)

Thereafter the estimated channel can be obtained as theeigenvectors of Ry

119896

via EVD processing [29]Note that since we focus on the link-level performance

the element of channel matrix H should be normalized andonly the additive noise and fast fading effects are taken intoconsideration to generate H If the array spacing is largerthan a half wave-length the elements of H would be lowlycorrelated and then the condition of (23) is easy to be satisfiedas reported elsewhere [30] where the BS AEs are usually sep-arated by several wave-lengths resulting in an uncorrelatedTx radiation pattern to preserve the pairwise orthogonalityamong channel vectors However in space-limitedM-MIMOsystems the pairwise orthogonality cannot be maintainedbecause the adjacent AE space is fixed normally at equal

or less than a half signal wave-length Consequently in thispaper we modify the EVD-based blind channel estimationscheme studied in Ngo and Larsson [29] The modifiedBCE approach can exploit the pairwise orthogonality via theparticular characteristics of PM-MIMO systems that is thepolarized cross-branch links in the system usually are uncor-related even though the adjacent AE spacing is set equal toor less than a half signal wave-length [17]

Based on other researches [14 16 31] an extension of thechannel matrix for PM-MIMO systems can be represented as

HPM-MIMO (119905)

= (

hTx1198601minusRx119860

1(119905) sdot sdot sdot hTx119860

1minusRx119860

(119905)

d

hTx119860119875minusRx119860

1(119905) sdot sdot sdot hTx119860

119875minusRx119860

(119905)

)

(24)

where

hTx119860119901minusRx119860

(119905) = radic

120578

119868

119868

sum

119894=1

(

ℎTx1198601199011198611minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198611(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198612(119905) ℎTx119860

1199011198612minusRx119860

1198612(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198612(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198613(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198613(119905) ℎTx119860

1199011198613minusRx119860

1198613(119905)

) (25)

Here 120578 and 119868 denote the transmit power and the numberof scatterers respectively Channel matrix (24) has a size of3119875-by-3 which is composed of 3-by-3 submatrices Eachsubmatrix holds the polarized cross-branch links between the119875th AE of Tx (the BS) and the th AE (UE) of receiver (Rx)Please note that throughout the paper theUE is assumedwithone AE that is = 1 The channel vectors of submatrix(25) are random and pairwise orthogonal because the polar-ized links from a Tx AE with three orthogonal branches toa single Rx branch are usually highly orthogonal [17] Con-sequently we can apply the EVD-based BCE via submatrixof (25) By redefining the covariance matrix of the receivedsignal as

Ry119896

≜ y119896y119867119896

= hTx119860119901minusRx119860

Rx119896

h119867Tx119860119901minusRx119860

+ Rn119896

(26)

the estimated channel can be obtained as the eigenvec-tors of Ry

119896

via EVD processing because the condition of(13)h119867Tx119860

119901minusRx119860

hTx119860119901minusRx119860

rarr I3is satisfied

5 Performance Verification

Table 1 lists the parameters settings of the performance veri-fication based on the LTE-A specification [32] The downlinkdata mapping for LTE-A resource blocks used in simulationsis demonstrated in Figure 10 which is based on theQO-STBC

symbol matrix of (5)We use the training sequences providedby [32] which are defined as

119903119897119899119904(119898) =

1

radic2(1 minus 2 sdot 119888 (2119898))

+ 1198951

radic2(1 minus 2 sdot 119888 (2119898 + 1))

(27)

where 119898 = 0 1 2119873max119863119871

119877119861

minus 1 The pilot density is 143and the initialization of 119888 is defined as

119888init = 210

sdot (7 sdot (119899119904+ 1) + 119897 + 1) sdot (2 sdot 119873

cellID + 1) + 2

sdot 119873cellID + 119873CP

(28)

where 119899119904is the slot number within a frame and

119873CP =

1 for normal CP

0 for extended CP(29)

Figure 11 depicts the probability densities of the HPBWgenerated in simulations where the HPBW can be effectivelykept as 50∘ on average by using the proposed AE selectionscheme of Figure 9 However the average HPBW extends byabout 15∘ when not considering the off bore-sight angle effectThis demonstrates that the proposed AE selection scheme isrobust that can optimize the generated beamwidth to avoidBF interference

Mobile Information Systems 11

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Branch A1B1 Branch A2B1

(a) Data mapping at Tx1198601199011198611

minus

minus

minus

minus

minus

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minus

minus

minus

minus

minus

minus

minus

minus

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minus

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PA1B2

PA1B2

PA1B2

PA1B2

1110

PA2B2

PA2B2

PA2B2

PA2B2

x3

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Branch A1B2 Branch A2B2

(b) Data mapping at Tx1198601199011198612

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xlowast471110

20 1 3 4 5 6 7 8 9Subframe

13121110

x4

x8

x12

x16

x20

x24

x28

x32

x36

x40

x44

x48

x2

x6

x10

x14

x18

x22

x26

x30

x34

x38

x42

x46

x52

x56

x60

x64

x68

x72

x76

x80

x84

x88

x92

x96

x50

x54

x58

x62

x66

x70

x74

x78

x82

x86

x90

x94

x100x104

x108

x112

x116

x120

x124

x128

x132

x136

x140

x144

x98

x102

x106

x110

x114

x118

x122

x126

x130

x134

x138

x142

xlowast97

xlowast101

xlowast105

xlowast109

xlowast113

xlowast117

xlowast121

xlowast125

xlowast129

xlowast133

xlowast137

xlowast141

xlowast99

xlowast103

xlowast107

xlowast111

xlowast115

xlowast119

xlowast123

xlowast127

xlowast131

xlowast135

xlowast139

xlowast143

Branch A1B3

(c) Data mapping at Tx1198601199011198613

Figure 10 Downlink data mapping of the LTE-A resource blocks used in the simulation

12 Mobile Information Systems

90

0005

001

0015

002

0025

003

With the proposed AE selection schemeWithout the proposed AE selection scheme

30 40 50 60 70 800

HPBW (deg)

Figure 11 Probability density of HPBW

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300

Case 2 PACE outdoor LOS 3kmhCase 3 PACE outdoor LOS 3kmh

Case 1 PACE outdoor LOS 3kmhCase 3 PACE outdoor NLOS 3kmhCase 2 PACE outdoor NLOS 3kmhCase 1 PACE outdoor NLOS 3kmh

EbN0 (dB)

Figure 12Users average BLERperformances based on the proposeddiversity system architecture

Figure 12 compares the usersrsquo average block error rate(BLER) performances obtained based on the proposeddiversity system architecture by using different transmissionschemes including Case 1 without STBC and TxBF Case2 with STBC only and Case 3 with STBC and TxBF viathe LTE pilot-assistant practical channel estimation (PACE)approach According to Figure 12 Case 1 has the worstperformance because there is no space-time coding and BFgain achieved About 17 dB of signal-to-noise ratio (SNR)gain at the target BLER can be achieved by Case 2 comparedwith Case 1 under the non-line-of-sight NLOS scenarioThere is about a 1 dB SNR gain that can be further achievedby employing the TxBF of Case 3 In addition the simulationresults under the LOS scenario are also provided as acomparison where almost 7 dB gain can be obtained whenthe LOS exists for those three cases

Next we simulate the BCE approaches and compare itsefficiency with the PACE based on the proposed diversitysystemarchitecture Figure 13 demonstrates the usersrsquo averageBLER via PACE and BCE approaches for three different

Table 1 Simulation parameters

Parameters ValueCarrier frequency 18GHzSystem bandwidth 20MHzFFT size 2048Number of data carriers 1200Number of samples in CP 144Subcarrier spacing 15 kHzBS antenna configuration(PM-MIMO) 1 MUX times 32 AE times 3 branches

BS AE spacing Half wavelengthUserrsquos antenna configuration 1 AE times 3 branches

Number of users 4 for 3D-BF diversity12 for 3D-BF multiplexing

Radius of userrsquos local area (119903UE) 15mAntenna type DipoleModulation QPSK

Number of scatterersOutdoor 4 clusters with 16scatterers per cluster (64 in

total)Scattering sphere radius 10mVelocity of UEs 3 60 and 120 kmhFading Flat

XPD value 58 dB and 97 dB for NLOSand LOS

Correlation 032 and 034 for NLOS andLOS

Rician 119870-factor 9 dB

userrsquos velocities including 3 60 and 120 kmh under theNLOS scenario An extension of other researches [14 31] isapplied to simulations of the polarized MIMO channel forwhich channel characteristics are also listed in Table 1 Wesee that the PACE performance decreases a lot due to highmobility at 60 and 120 kmh which indicates that the numberof pilots is not enough to compensate the channel correctlyin an environment with fast time-varying phase responseThe pilot density is 143 for PACE scheme and by consid-ering the trade-off regarding spectrum efficiency BCE thatrequires no or a minimal number of pilots might be betteremployed Figure 13 additionally shows the performances ofBCE schemes where performance is found that is not relevantto the userrsquos velocity Compared with the BCE reported byNgo and Larsson [29] our proposed BCE performance isbetter because the EVD is based on low correlated submatrixand has less complexity for doing the EVD based on asubmatrix with a smaller size Due to no pilot contaminationby BCE approach the proposed BCE outperforms PACEfor a velocity of 3 kmh when 119864

119887119873

0is less than 25 dB

However BCE has a higher complexity than PACE and itis condition constraint Again according to Figure 13 BCEperforms worse than PACE with a velocity of 3 kmh when119864119887119873

0is larger than 25 dB and the trend of error floor for

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

10minus1

100

UEs

aver

age B

LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia

International Journal of

Biomedical Imaging

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mobile Information Systems 9

No No

No

Start

Detection of incident signalfrom K UEs y1(t) y2(t) yK(t)

For yk(t) find max(120572k 120573k 120574k)

If 120572k is maximum If 120573k is maximum

YesYes

If yA119901B119887k

(t) belongs to cell-edge UE

Select AEs for yA119901B119887k

(t) and explore

diversity gain by STBC with 3D-BF

Select AEs for yA119901B119887k

(t) and explore

multiplexing gain by 3D-BF

k = k + 1

If k gt K

If k gt K

Yes

End

No

Categorize yk(t) to yA119901B3k

(t) max(120572k 120573k 120574k) = 120572k

Categorize yk(t) to yA119901B1k

(t) max(120572k 120573k 120574k) = 120574k

Categorize yk(t) to yA119901B2k

(t) max(120572k 120573k 120574k) = 120573k

Yes

Yes

No

Figure 9 Flowchart of the proposed AE selection scheme for PM-MIMO system

The BCE approach which requires no or a minimalnumber of pilots needs to be applied in M-MIMO systemsOne of the BCE strategies is based on eigenvalue decompo-sition (EVD) for the covariance matrix of a received signalthat needs to preserve pairwise orthogonality among channelvectors [27ndash29] Let us define an M-MIMO system model as

y119896= Hx

119896+ n

119896 (20)

where x119896is the transmitted symbolsH is an119872-by-119873 channel

matrix between the BS and the 119896th UE and n119896denotes

the additive white noise The covariance matrix of thereceived signal is then defined by

Ry119896

≜ y119896y119867119896

= HRx119896

H119867

+ Rn119896

(21)

where 119867 represents the Hermitian Transpose operationAdditionally multiplyingH at both sides of (21) we have

Ry119896

H = HRx119896

H119867H +H (22)

10 Mobile Information Systems

From the law of large number the channel vectors betweenthe BS and the deployed UEs become very long random andpairwise orthogonal which satisfies the condition

1

119872H119867H 997888rarr I

119873 as 119872 997888rarr infin (23)

Thereafter the estimated channel can be obtained as theeigenvectors of Ry

119896

via EVD processing [29]Note that since we focus on the link-level performance

the element of channel matrix H should be normalized andonly the additive noise and fast fading effects are taken intoconsideration to generate H If the array spacing is largerthan a half wave-length the elements of H would be lowlycorrelated and then the condition of (23) is easy to be satisfiedas reported elsewhere [30] where the BS AEs are usually sep-arated by several wave-lengths resulting in an uncorrelatedTx radiation pattern to preserve the pairwise orthogonalityamong channel vectors However in space-limitedM-MIMOsystems the pairwise orthogonality cannot be maintainedbecause the adjacent AE space is fixed normally at equal

or less than a half signal wave-length Consequently in thispaper we modify the EVD-based blind channel estimationscheme studied in Ngo and Larsson [29] The modifiedBCE approach can exploit the pairwise orthogonality via theparticular characteristics of PM-MIMO systems that is thepolarized cross-branch links in the system usually are uncor-related even though the adjacent AE spacing is set equal toor less than a half signal wave-length [17]

Based on other researches [14 16 31] an extension of thechannel matrix for PM-MIMO systems can be represented as

HPM-MIMO (119905)

= (

hTx1198601minusRx119860

1(119905) sdot sdot sdot hTx119860

1minusRx119860

(119905)

d

hTx119860119875minusRx119860

1(119905) sdot sdot sdot hTx119860

119875minusRx119860

(119905)

)

(24)

where

hTx119860119901minusRx119860

(119905) = radic

120578

119868

119868

sum

119894=1

(

ℎTx1198601199011198611minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198611(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198612(119905) ℎTx119860

1199011198612minusRx119860

1198612(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198612(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198613(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198613(119905) ℎTx119860

1199011198613minusRx119860

1198613(119905)

) (25)

Here 120578 and 119868 denote the transmit power and the numberof scatterers respectively Channel matrix (24) has a size of3119875-by-3 which is composed of 3-by-3 submatrices Eachsubmatrix holds the polarized cross-branch links between the119875th AE of Tx (the BS) and the th AE (UE) of receiver (Rx)Please note that throughout the paper theUE is assumedwithone AE that is = 1 The channel vectors of submatrix(25) are random and pairwise orthogonal because the polar-ized links from a Tx AE with three orthogonal branches toa single Rx branch are usually highly orthogonal [17] Con-sequently we can apply the EVD-based BCE via submatrixof (25) By redefining the covariance matrix of the receivedsignal as

Ry119896

≜ y119896y119867119896

= hTx119860119901minusRx119860

Rx119896

h119867Tx119860119901minusRx119860

+ Rn119896

(26)

the estimated channel can be obtained as the eigenvec-tors of Ry

119896

via EVD processing because the condition of(13)h119867Tx119860

119901minusRx119860

hTx119860119901minusRx119860

rarr I3is satisfied

5 Performance Verification

Table 1 lists the parameters settings of the performance veri-fication based on the LTE-A specification [32] The downlinkdata mapping for LTE-A resource blocks used in simulationsis demonstrated in Figure 10 which is based on theQO-STBC

symbol matrix of (5)We use the training sequences providedby [32] which are defined as

119903119897119899119904(119898) =

1

radic2(1 minus 2 sdot 119888 (2119898))

+ 1198951

radic2(1 minus 2 sdot 119888 (2119898 + 1))

(27)

where 119898 = 0 1 2119873max119863119871

119877119861

minus 1 The pilot density is 143and the initialization of 119888 is defined as

119888init = 210

sdot (7 sdot (119899119904+ 1) + 119897 + 1) sdot (2 sdot 119873

cellID + 1) + 2

sdot 119873cellID + 119873CP

(28)

where 119899119904is the slot number within a frame and

119873CP =

1 for normal CP

0 for extended CP(29)

Figure 11 depicts the probability densities of the HPBWgenerated in simulations where the HPBW can be effectivelykept as 50∘ on average by using the proposed AE selectionscheme of Figure 9 However the average HPBW extends byabout 15∘ when not considering the off bore-sight angle effectThis demonstrates that the proposed AE selection scheme isrobust that can optimize the generated beamwidth to avoidBF interference

Mobile Information Systems 11

PA2B1

PA2B1

PA2B1

PA2B1

0 1 3 4 5 6 7 8 9

0

1

9

8

7

6

5

4

3

2

Subframe

xlowast1

xlowast5

xlowast9

xlowast17

xlowast13

xlowast21

xlowast25

xlowast29

xlowast33

xlowast37

xlowast41

xlowast45

xlowast51

xlowast55

xlowast59

xlowast63

xlowast67

xlowast71

xlowast75

xlowast79

xlowast83

xlowast87

xlowast91

xlowast95

xlowast49

xlowast53

xlowast57

xlowast61

xlowast65

xlowast69

xlowast73

xlowast77

xlowast81

xlowast85

xlowast89

xlowast93

xlowast3

xlowast7

xlowast11

xlowast19

xlowast15

xlowast23

xlowast27

xlowast31

xlowast35

xlowast39

xlowast43

xlowast47

PA1B1

PA1B1

PA1B1

PA1B1

Reso

urce

blo

ck

13121111

10

10

x2

x6

x10

x14

x18

x22

x26

x30

x34

x38

x42

x46

x4

x8

x12

x16

x20

x24

x28

x32

x36

x40

x44

x48

x50

x54

x58

x62

x66

x70

x74

x78

x82

x86

x90

x94

x52

x56

x60

x64

x68

x72

x76

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Branch A1B1 Branch A2B1

(a) Data mapping at Tx1198601199011198611

minus

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urce

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ck

01

98765432

xlowast4

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PA1B2

PA1B2

PA1B2

PA1B2

1110

PA2B2

PA2B2

PA2B2

PA2B2

x3

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minus

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urce

blo

ck

01

98765432

xlowast4

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20 1 3 4 5 6 7 8 9Subframe

131211131211 1020 1 3 4 5 6 7 8 9Subframe

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x101

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x113

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x141

xlowast98

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xlowast140

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minus minus

minus

minus

minus

minus

minus

minus

minus

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minus

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minus

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x97

x101

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Branch A1B2 Branch A2B2

(b) Data mapping at Tx1198601199011198612

xlowast49xlowast53

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Reso

urce

blo

ck

01

98765432

xlowast3

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PA1B3

PA1B3

PA1B3

PA1B3

1110

20 1 3 4 5 6 7 8 9Subframe

13121110

Branch A2B3

PA2B3PA2B3

PA2B3 PA2B3

x4

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x98

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xlowast1

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xlowast29

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xlowast41

xlowast45

Reso

urce

blo

ck

01

98765432

xlowast3

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xlowast471110

20 1 3 4 5 6 7 8 9Subframe

13121110

x4

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xlowast135

xlowast139

xlowast143

Branch A1B3

(c) Data mapping at Tx1198601199011198613

Figure 10 Downlink data mapping of the LTE-A resource blocks used in the simulation

12 Mobile Information Systems

90

0005

001

0015

002

0025

003

With the proposed AE selection schemeWithout the proposed AE selection scheme

30 40 50 60 70 800

HPBW (deg)

Figure 11 Probability density of HPBW

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300

Case 2 PACE outdoor LOS 3kmhCase 3 PACE outdoor LOS 3kmh

Case 1 PACE outdoor LOS 3kmhCase 3 PACE outdoor NLOS 3kmhCase 2 PACE outdoor NLOS 3kmhCase 1 PACE outdoor NLOS 3kmh

EbN0 (dB)

Figure 12Users average BLERperformances based on the proposeddiversity system architecture

Figure 12 compares the usersrsquo average block error rate(BLER) performances obtained based on the proposeddiversity system architecture by using different transmissionschemes including Case 1 without STBC and TxBF Case2 with STBC only and Case 3 with STBC and TxBF viathe LTE pilot-assistant practical channel estimation (PACE)approach According to Figure 12 Case 1 has the worstperformance because there is no space-time coding and BFgain achieved About 17 dB of signal-to-noise ratio (SNR)gain at the target BLER can be achieved by Case 2 comparedwith Case 1 under the non-line-of-sight NLOS scenarioThere is about a 1 dB SNR gain that can be further achievedby employing the TxBF of Case 3 In addition the simulationresults under the LOS scenario are also provided as acomparison where almost 7 dB gain can be obtained whenthe LOS exists for those three cases

Next we simulate the BCE approaches and compare itsefficiency with the PACE based on the proposed diversitysystemarchitecture Figure 13 demonstrates the usersrsquo averageBLER via PACE and BCE approaches for three different

Table 1 Simulation parameters

Parameters ValueCarrier frequency 18GHzSystem bandwidth 20MHzFFT size 2048Number of data carriers 1200Number of samples in CP 144Subcarrier spacing 15 kHzBS antenna configuration(PM-MIMO) 1 MUX times 32 AE times 3 branches

BS AE spacing Half wavelengthUserrsquos antenna configuration 1 AE times 3 branches

Number of users 4 for 3D-BF diversity12 for 3D-BF multiplexing

Radius of userrsquos local area (119903UE) 15mAntenna type DipoleModulation QPSK

Number of scatterersOutdoor 4 clusters with 16scatterers per cluster (64 in

total)Scattering sphere radius 10mVelocity of UEs 3 60 and 120 kmhFading Flat

XPD value 58 dB and 97 dB for NLOSand LOS

Correlation 032 and 034 for NLOS andLOS

Rician 119870-factor 9 dB

userrsquos velocities including 3 60 and 120 kmh under theNLOS scenario An extension of other researches [14 31] isapplied to simulations of the polarized MIMO channel forwhich channel characteristics are also listed in Table 1 Wesee that the PACE performance decreases a lot due to highmobility at 60 and 120 kmh which indicates that the numberof pilots is not enough to compensate the channel correctlyin an environment with fast time-varying phase responseThe pilot density is 143 for PACE scheme and by consid-ering the trade-off regarding spectrum efficiency BCE thatrequires no or a minimal number of pilots might be betteremployed Figure 13 additionally shows the performances ofBCE schemes where performance is found that is not relevantto the userrsquos velocity Compared with the BCE reported byNgo and Larsson [29] our proposed BCE performance isbetter because the EVD is based on low correlated submatrixand has less complexity for doing the EVD based on asubmatrix with a smaller size Due to no pilot contaminationby BCE approach the proposed BCE outperforms PACEfor a velocity of 3 kmh when 119864

119887119873

0is less than 25 dB

However BCE has a higher complexity than PACE and itis condition constraint Again according to Figure 13 BCEperforms worse than PACE with a velocity of 3 kmh when119864119887119873

0is larger than 25 dB and the trend of error floor for

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

10minus1

100

UEs

aver

age B

LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia

International Journal of

Biomedical Imaging

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

Advances in

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RoboticsJournal of

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Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

10 Mobile Information Systems

From the law of large number the channel vectors betweenthe BS and the deployed UEs become very long random andpairwise orthogonal which satisfies the condition

1

119872H119867H 997888rarr I

119873 as 119872 997888rarr infin (23)

Thereafter the estimated channel can be obtained as theeigenvectors of Ry

119896

via EVD processing [29]Note that since we focus on the link-level performance

the element of channel matrix H should be normalized andonly the additive noise and fast fading effects are taken intoconsideration to generate H If the array spacing is largerthan a half wave-length the elements of H would be lowlycorrelated and then the condition of (23) is easy to be satisfiedas reported elsewhere [30] where the BS AEs are usually sep-arated by several wave-lengths resulting in an uncorrelatedTx radiation pattern to preserve the pairwise orthogonalityamong channel vectors However in space-limitedM-MIMOsystems the pairwise orthogonality cannot be maintainedbecause the adjacent AE space is fixed normally at equal

or less than a half signal wave-length Consequently in thispaper we modify the EVD-based blind channel estimationscheme studied in Ngo and Larsson [29] The modifiedBCE approach can exploit the pairwise orthogonality via theparticular characteristics of PM-MIMO systems that is thepolarized cross-branch links in the system usually are uncor-related even though the adjacent AE spacing is set equal toor less than a half signal wave-length [17]

Based on other researches [14 16 31] an extension of thechannel matrix for PM-MIMO systems can be represented as

HPM-MIMO (119905)

= (

hTx1198601minusRx119860

1(119905) sdot sdot sdot hTx119860

1minusRx119860

(119905)

d

hTx119860119875minusRx119860

1(119905) sdot sdot sdot hTx119860

119875minusRx119860

(119905)

)

(24)

where

hTx119860119901minusRx119860

(119905) = radic

120578

119868

119868

sum

119894=1

(

ℎTx1198601199011198611minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198611(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198611(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198612(119905) ℎTx119860

1199011198612minusRx119860

1198612(119905) radic120583 sdot ℎTx119860

1199011198613minusRx119860

1198612(119905)

radic120583 sdot ℎTx1198601199011198611minusRx119860

1198613(119905) radic120583 sdot ℎTx119860

1199011198612minusRx119860

1198613(119905) ℎTx119860

1199011198613minusRx119860

1198613(119905)

) (25)

Here 120578 and 119868 denote the transmit power and the numberof scatterers respectively Channel matrix (24) has a size of3119875-by-3 which is composed of 3-by-3 submatrices Eachsubmatrix holds the polarized cross-branch links between the119875th AE of Tx (the BS) and the th AE (UE) of receiver (Rx)Please note that throughout the paper theUE is assumedwithone AE that is = 1 The channel vectors of submatrix(25) are random and pairwise orthogonal because the polar-ized links from a Tx AE with three orthogonal branches toa single Rx branch are usually highly orthogonal [17] Con-sequently we can apply the EVD-based BCE via submatrixof (25) By redefining the covariance matrix of the receivedsignal as

Ry119896

≜ y119896y119867119896

= hTx119860119901minusRx119860

Rx119896

h119867Tx119860119901minusRx119860

+ Rn119896

(26)

the estimated channel can be obtained as the eigenvec-tors of Ry

119896

via EVD processing because the condition of(13)h119867Tx119860

119901minusRx119860

hTx119860119901minusRx119860

rarr I3is satisfied

5 Performance Verification

Table 1 lists the parameters settings of the performance veri-fication based on the LTE-A specification [32] The downlinkdata mapping for LTE-A resource blocks used in simulationsis demonstrated in Figure 10 which is based on theQO-STBC

symbol matrix of (5)We use the training sequences providedby [32] which are defined as

119903119897119899119904(119898) =

1

radic2(1 minus 2 sdot 119888 (2119898))

+ 1198951

radic2(1 minus 2 sdot 119888 (2119898 + 1))

(27)

where 119898 = 0 1 2119873max119863119871

119877119861

minus 1 The pilot density is 143and the initialization of 119888 is defined as

119888init = 210

sdot (7 sdot (119899119904+ 1) + 119897 + 1) sdot (2 sdot 119873

cellID + 1) + 2

sdot 119873cellID + 119873CP

(28)

where 119899119904is the slot number within a frame and

119873CP =

1 for normal CP

0 for extended CP(29)

Figure 11 depicts the probability densities of the HPBWgenerated in simulations where the HPBW can be effectivelykept as 50∘ on average by using the proposed AE selectionscheme of Figure 9 However the average HPBW extends byabout 15∘ when not considering the off bore-sight angle effectThis demonstrates that the proposed AE selection scheme isrobust that can optimize the generated beamwidth to avoidBF interference

Mobile Information Systems 11

PA2B1

PA2B1

PA2B1

PA2B1

0 1 3 4 5 6 7 8 9

0

1

9

8

7

6

5

4

3

2

Subframe

xlowast1

xlowast5

xlowast9

xlowast17

xlowast13

xlowast21

xlowast25

xlowast29

xlowast33

xlowast37

xlowast41

xlowast45

xlowast51

xlowast55

xlowast59

xlowast63

xlowast67

xlowast71

xlowast75

xlowast79

xlowast83

xlowast87

xlowast91

xlowast95

xlowast49

xlowast53

xlowast57

xlowast61

xlowast65

xlowast69

xlowast73

xlowast77

xlowast81

xlowast85

xlowast89

xlowast93

xlowast3

xlowast7

xlowast11

xlowast19

xlowast15

xlowast23

xlowast27

xlowast31

xlowast35

xlowast39

xlowast43

xlowast47

PA1B1

PA1B1

PA1B1

PA1B1

Reso

urce

blo

ck

13121111

10

10

x2

x6

x10

x14

x18

x22

x26

x30

x34

x38

x42

x46

x4

x8

x12

x16

x20

x24

x28

x32

x36

x40

x44

x48

x50

x54

x58

x62

x66

x70

x74

x78

x82

x86

x90

x94

x52

x56

x60

x64

x68

x72

x76

x80

x84

x88

x92

x96

x98

x102

x106

x110

x114

x118

x122

x126

x130

x134

x138

x142

x100

x104

x108

x112

x116

x120

x124

x128

x132

x136

x140

x144

xlowast99

xlowast103

xlowast107

xlowast111

xlowast115

xlowast119

xlowast123

xlowast127

xlowast131

xlowast135

xlowast139

xlowast143

xlowast97

xlowast101

xlowast105

xlowast109

xlowast113

xlowast117

xlowast121

xlowast125

xlowast129

xlowast133

xlowast137

xlowast14120 1 3 4 5 6 7 8 9

0

1

9

8

7

6

5

4

3

2

Subframe

xlowast1

xlowast5

xlowast9

xlowast17

xlowast13

xlowast21

xlowast25

xlowast29

xlowast33

xlowast37

xlowast41

xlowast45

xlowast51

xlowast55

xlowast59

xlowast63

xlowast67

xlowast71

xlowast75

xlowast79

xlowast83

xlowast87

xlowast91

xlowast95

xlowast49

xlowast53

xlowast57

xlowast61

xlowast65

xlowast69

xlowast73

xlowast77

xlowast81

xlowast85

xlowast89

xlowast93

xlowast3

xlowast7

xlowast11

xlowast19

xlowast15

xlowast23

xlowast27

xlowast31

xlowast35

xlowast39

xlowast43

xlowast47

Reso

urce

blo

ck

13121111

10

10

x2

x6

x10

x14

x18

x22

x26

x30

x34

x38

x42

x46

x4

x8

x12

x16

x20

x24

x28

x32

x36

x40

x44

x48

x50

x54

x58

x62

x66

x70

x74

x78

x82

x86

x90

x94

x52

x56

x60

x64

x68

x72

x76

x80

x84

x88

x92

x96

x98

x102

x106

x110

x114

x118

x122

x126

x130

x134

x138

x142

x100

x104

x108

x112

x116

x120

x124

x128

x132

x136

x140

x144

xlowast99

xlowast103

xlowast107

xlowast111

xlowast115

xlowast119

xlowast123

xlowast127

xlowast131

xlowast135

xlowast139

xlowast143

xlowast97

xlowast101

xlowast105

xlowast109

xlowast113

xlowast117

xlowast121

xlowast125

xlowast129

xlowast133

xlowast137

xlowast1412

Branch A1B1 Branch A2B1

(a) Data mapping at Tx1198601199011198611

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

xlowast50

xlowast54

xlowast58

xlowast62

xlowast66

xlowast70

xlowast74

xlowast78

xlowast82

xlowast86

xlowast90

xlowast94

xlowast52

xlowast56

xlowast52

xlowast56

xlowast52

xlowast56

xlowast52

xlowast56

xlowast56

xlowast52

xlowast56

xlowast96

xlowast2

xlowast6

xlowast10

xlowast18

xlowast14

xlowast22

xlowast26

xlowast30

xlowast34

xlowast38

xlowast42

xlowast46

Reso

urce

blo

ck

01

98765432

xlowast4

xlowast8

xlowast12

xlowast20

xlowast16

xlowast24

xlowast28

xlowast32

xlowast36

xlowast40

xlowast44

xlowast48

PA1B2

PA1B2

PA1B2

PA1B2

1110

PA2B2

PA2B2

PA2B2

PA2B2

x3

x7

x11

x15

x19

x23

x27

x31

x35

x39

x43

x47

x1

x5

x9

x13

x17

x21

x25

x29

x33

x37

x41

x45

x51

x55

x59

x63

x67

x71

x75

x79

x83

x87

x91

x95

x49

x53

x57

x61

x65

x69

x73

x77

x81

x85

x89

x93

x99

x103

x107

x111

x115

x119

x123

x127

x131

x135

x139

x143

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

xlowast50

xlowast54

xlowast58

xlowast62

xlowast66

xlowast70

xlowast74

xlowast78

xlowast82

xlowast86

xlowast90

xlowast94

xlowast52

xlowast56

xlowast52

xlowast56

xlowast52

xlowast56

xlowast52

xlowast56

xlowast56

xlowast52

xlowast56

xlowast96

xlowast2

xlowast6

xlowast10

xlowast18

xlowast14

xlowast22

xlowast26

xlowast30

xlowast34

xlowast38

xlowast42

xlowast46

Reso

urce

blo

ck

01

98765432

xlowast4

xlowast8

xlowast12

xlowast20

xlowast16

xlowast24

xlowast28

xlowast32

xlowast36

xlowast40

xlowast44

xlowast481110

20 1 3 4 5 6 7 8 9Subframe

131211131211 1020 1 3 4 5 6 7 8 9Subframe

10

x3

x7

x11

x15

x19

x23

x27

x31

x35

x39

x43

x47

x1

x5

x9

x13

x17

x21

x25

x29

x33

x37

x41

x45

x51

x55

x59

x63

x67

x71

x75

x79

x83

x87

x91

x95

x49

x53

x57

x61

x65

x69

x73

x77

x81

x85

x89

x93

x99

x103

x107

x111

x115

x119

x123

x127

x131

x135

x139

x143

x97

x101

x105

x109

x113

x117

x121

x125

x129

x133

x137

x141

xlowast98

xlowast102

xlowast106

xlowast110

xlowast114

xlowast118

xlowast122

xlowast126

xlowast130

xlowast134

xlowast138

xlowast142

xlowast100

xlowast104

xlowast108

xlowast112

xlowast116

xlowast120

xlowast124

xlowast128

xlowast132

xlowast136

xlowast140

xlowast144

minus minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

x97

x101

x105

x109

x113

x117

x121

x125

x129

x133

x137

x141

xlowast98

xlowast102

xlowast106

xlowast110

xlowast114

xlowast118

xlowast122

xlowast126

xlowast130

xlowast134

xlowast138

xlowast142

xlowast100

xlowast104

xlowast108

xlowast112

xlowast116

xlowast120

xlowast124

xlowast128

xlowast132

xlowast136

xlowast140

xlowast144

Branch A1B2 Branch A2B2

(b) Data mapping at Tx1198601199011198612

xlowast49xlowast53

xlowast57

xlowast61

xlowast65

xlowast69

xlowast73

xlowast77

xlowast81

xlowast85

xlowast89

xlowast93

xlowast51xlowast55

xlowast59

xlowast63

xlowast67

xlowast71

xlowast75

xlowast79

xlowast83

xlowast87

xlowast91

xlowast95

xlowast1

xlowast5

xlowast9

xlowast17

xlowast13

xlowast21

xlowast25

xlowast29

xlowast33

xlowast37

xlowast41

xlowast45

Reso

urce

blo

ck

01

98765432

xlowast3

xlowast7

xlowast11

xlowast19

xlowast15

xlowast23

xlowast27

xlowast31

xlowast35

xlowast39

xlowast43

xlowast47

PA1B3

PA1B3

PA1B3

PA1B3

1110

20 1 3 4 5 6 7 8 9Subframe

13121110

Branch A2B3

PA2B3PA2B3

PA2B3 PA2B3

x4

x8

x12

x16

x20

x24

x28

x32

x36

x40

x44

x48

x2

x6

x10

x14

x18

x22

x26

x30

x34

x38

x42

x46

x52

x56

x60

x64

x68

x72

x76

x80

x84

x88

x92

x96

x50

x54

x58

x62

x66

x70

x74

x78

x82

x86

x90

x94

x100x104

x108

x112

x116

x120

x124

x128

x132

x136

x140

x144

x98

x102

x106

x110

x114

x118

x122

x126

x130

x134

x138

x142

xlowast97

xlowast101

xlowast105

xlowast109

xlowast113

xlowast117

xlowast121

xlowast125

xlowast129

xlowast133

xlowast137

xlowast141

xlowast99

xlowast103

xlowast107

xlowast111

xlowast115

xlowast119

xlowast123

xlowast127

xlowast131

xlowast135

xlowast139

xlowast143

xlowast49xlowast53

xlowast57

xlowast61

xlowast65

xlowast69

xlowast73

xlowast77

xlowast81

xlowast85

xlowast89

xlowast93

xlowast51xlowast55

xlowast59

xlowast63

xlowast67

xlowast71

xlowast75

xlowast79

xlowast83

xlowast87

xlowast91

xlowast95

xlowast1

xlowast5

xlowast9

xlowast17

xlowast13

xlowast21

xlowast25

xlowast29

xlowast33

xlowast37

xlowast41

xlowast45

Reso

urce

blo

ck

01

98765432

xlowast3

xlowast7

xlowast11

xlowast19

xlowast15

xlowast23

xlowast27

xlowast31

xlowast35

xlowast39

xlowast43

xlowast471110

20 1 3 4 5 6 7 8 9Subframe

13121110

x4

x8

x12

x16

x20

x24

x28

x32

x36

x40

x44

x48

x2

x6

x10

x14

x18

x22

x26

x30

x34

x38

x42

x46

x52

x56

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x64

x68

x72

x76

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x84

x88

x92

x96

x50

x54

x58

x62

x66

x70

x74

x78

x82

x86

x90

x94

x100x104

x108

x112

x116

x120

x124

x128

x132

x136

x140

x144

x98

x102

x106

x110

x114

x118

x122

x126

x130

x134

x138

x142

xlowast97

xlowast101

xlowast105

xlowast109

xlowast113

xlowast117

xlowast121

xlowast125

xlowast129

xlowast133

xlowast137

xlowast141

xlowast99

xlowast103

xlowast107

xlowast111

xlowast115

xlowast119

xlowast123

xlowast127

xlowast131

xlowast135

xlowast139

xlowast143

Branch A1B3

(c) Data mapping at Tx1198601199011198613

Figure 10 Downlink data mapping of the LTE-A resource blocks used in the simulation

12 Mobile Information Systems

90

0005

001

0015

002

0025

003

With the proposed AE selection schemeWithout the proposed AE selection scheme

30 40 50 60 70 800

HPBW (deg)

Figure 11 Probability density of HPBW

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300

Case 2 PACE outdoor LOS 3kmhCase 3 PACE outdoor LOS 3kmh

Case 1 PACE outdoor LOS 3kmhCase 3 PACE outdoor NLOS 3kmhCase 2 PACE outdoor NLOS 3kmhCase 1 PACE outdoor NLOS 3kmh

EbN0 (dB)

Figure 12Users average BLERperformances based on the proposeddiversity system architecture

Figure 12 compares the usersrsquo average block error rate(BLER) performances obtained based on the proposeddiversity system architecture by using different transmissionschemes including Case 1 without STBC and TxBF Case2 with STBC only and Case 3 with STBC and TxBF viathe LTE pilot-assistant practical channel estimation (PACE)approach According to Figure 12 Case 1 has the worstperformance because there is no space-time coding and BFgain achieved About 17 dB of signal-to-noise ratio (SNR)gain at the target BLER can be achieved by Case 2 comparedwith Case 1 under the non-line-of-sight NLOS scenarioThere is about a 1 dB SNR gain that can be further achievedby employing the TxBF of Case 3 In addition the simulationresults under the LOS scenario are also provided as acomparison where almost 7 dB gain can be obtained whenthe LOS exists for those three cases

Next we simulate the BCE approaches and compare itsefficiency with the PACE based on the proposed diversitysystemarchitecture Figure 13 demonstrates the usersrsquo averageBLER via PACE and BCE approaches for three different

Table 1 Simulation parameters

Parameters ValueCarrier frequency 18GHzSystem bandwidth 20MHzFFT size 2048Number of data carriers 1200Number of samples in CP 144Subcarrier spacing 15 kHzBS antenna configuration(PM-MIMO) 1 MUX times 32 AE times 3 branches

BS AE spacing Half wavelengthUserrsquos antenna configuration 1 AE times 3 branches

Number of users 4 for 3D-BF diversity12 for 3D-BF multiplexing

Radius of userrsquos local area (119903UE) 15mAntenna type DipoleModulation QPSK

Number of scatterersOutdoor 4 clusters with 16scatterers per cluster (64 in

total)Scattering sphere radius 10mVelocity of UEs 3 60 and 120 kmhFading Flat

XPD value 58 dB and 97 dB for NLOSand LOS

Correlation 032 and 034 for NLOS andLOS

Rician 119870-factor 9 dB

userrsquos velocities including 3 60 and 120 kmh under theNLOS scenario An extension of other researches [14 31] isapplied to simulations of the polarized MIMO channel forwhich channel characteristics are also listed in Table 1 Wesee that the PACE performance decreases a lot due to highmobility at 60 and 120 kmh which indicates that the numberof pilots is not enough to compensate the channel correctlyin an environment with fast time-varying phase responseThe pilot density is 143 for PACE scheme and by consid-ering the trade-off regarding spectrum efficiency BCE thatrequires no or a minimal number of pilots might be betteremployed Figure 13 additionally shows the performances ofBCE schemes where performance is found that is not relevantto the userrsquos velocity Compared with the BCE reported byNgo and Larsson [29] our proposed BCE performance isbetter because the EVD is based on low correlated submatrixand has less complexity for doing the EVD based on asubmatrix with a smaller size Due to no pilot contaminationby BCE approach the proposed BCE outperforms PACEfor a velocity of 3 kmh when 119864

119887119873

0is less than 25 dB

However BCE has a higher complexity than PACE and itis condition constraint Again according to Figure 13 BCEperforms worse than PACE with a velocity of 3 kmh when119864119887119873

0is larger than 25 dB and the trend of error floor for

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

10minus1

100

UEs

aver

age B

LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

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Distributed Sensor Networks

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Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

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HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

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International Journal of

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ArtificialNeural Systems

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RoboticsJournal of

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mobile Information Systems 11

PA2B1

PA2B1

PA2B1

PA2B1

0 1 3 4 5 6 7 8 9

0

1

9

8

7

6

5

4

3

2

Subframe

xlowast1

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PA1B1

PA1B1

PA1B1

PA1B1

Reso

urce

blo

ck

13121111

10

10

x2

x6

x10

x14

x18

x22

x26

x30

x34

x38

x42

x46

x4

x8

x12

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x88

x92

x96

x98

x102

x106

x110

x114

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x122

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x130

x134

x138

x142

x100

x104

x108

x112

x116

x120

x124

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x132

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x140

x144

xlowast99

xlowast103

xlowast107

xlowast111

xlowast115

xlowast119

xlowast123

xlowast127

xlowast131

xlowast135

xlowast139

xlowast143

xlowast97

xlowast101

xlowast105

xlowast109

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xlowast117

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xlowast14120 1 3 4 5 6 7 8 9

0

1

9

8

7

6

5

4

3

2

Subframe

xlowast1

xlowast5

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xlowast27

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Reso

urce

blo

ck

13121111

10

10

x2

x6

x10

x14

x18

x22

x26

x30

x34

x38

x42

x46

x4

x8

x12

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x36

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x44

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x50

x54

x58

x62

x66

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x86

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x94

x52

x56

x60

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x72

x76

x80

x84

x88

x92

x96

x98

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x106

x110

x114

x118

x122

x126

x130

x134

x138

x142

x100

x104

x108

x112

x116

x120

x124

x128

x132

x136

x140

x144

xlowast99

xlowast103

xlowast107

xlowast111

xlowast115

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xlowast97

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xlowast133

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xlowast1412

Branch A1B1 Branch A2B1

(a) Data mapping at Tx1198601199011198611

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

xlowast50

xlowast54

xlowast58

xlowast62

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xlowast70

xlowast74

xlowast78

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xlowast90

xlowast94

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xlowast56

xlowast52

xlowast56

xlowast52

xlowast56

xlowast52

xlowast56

xlowast56

xlowast52

xlowast56

xlowast96

xlowast2

xlowast6

xlowast10

xlowast18

xlowast14

xlowast22

xlowast26

xlowast30

xlowast34

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xlowast42

xlowast46

Reso

urce

blo

ck

01

98765432

xlowast4

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xlowast20

xlowast16

xlowast24

xlowast28

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xlowast44

xlowast48

PA1B2

PA1B2

PA1B2

PA1B2

1110

PA2B2

PA2B2

PA2B2

PA2B2

x3

x7

x11

x15

x19

x23

x27

x31

x35

x39

x43

x47

x1

x5

x9

x13

x17

x21

x25

x29

x33

x37

x41

x45

x51

x55

x59

x63

x67

x71

x75

x79

x83

x87

x91

x95

x49

x53

x57

x61

x65

x69

x73

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x81

x85

x89

x93

x99

x103

x107

x111

x115

x119

x123

x127

x131

x135

x139

x143

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

xlowast50

xlowast54

xlowast58

xlowast62

xlowast66

xlowast70

xlowast74

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xlowast52

xlowast56

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xlowast56

xlowast56

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xlowast6

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xlowast22

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Reso

urce

blo

ck

01

98765432

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20 1 3 4 5 6 7 8 9Subframe

131211131211 1020 1 3 4 5 6 7 8 9Subframe

10

x3

x7

x11

x15

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x27

x31

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x47

x1

x5

x9

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x91

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x97

x101

x105

x109

x113

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x121

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x133

x137

x141

xlowast98

xlowast102

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xlowast110

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xlowast130

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xlowast142

xlowast100

xlowast104

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xlowast112

xlowast116

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xlowast124

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xlowast132

xlowast136

xlowast140

xlowast144

minus minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

minus

x97

x101

x105

x109

x113

x117

x121

x125

x129

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x137

x141

xlowast98

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xlowast124

xlowast128

xlowast132

xlowast136

xlowast140

xlowast144

Branch A1B2 Branch A2B2

(b) Data mapping at Tx1198601199011198612

xlowast49xlowast53

xlowast57

xlowast61

xlowast65

xlowast69

xlowast73

xlowast77

xlowast81

xlowast85

xlowast89

xlowast93

xlowast51xlowast55

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xlowast45

Reso

urce

blo

ck

01

98765432

xlowast3

xlowast7

xlowast11

xlowast19

xlowast15

xlowast23

xlowast27

xlowast31

xlowast35

xlowast39

xlowast43

xlowast47

PA1B3

PA1B3

PA1B3

PA1B3

1110

20 1 3 4 5 6 7 8 9Subframe

13121110

Branch A2B3

PA2B3PA2B3

PA2B3 PA2B3

x4

x8

x12

x16

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x28

x32

x36

x40

x44

x48

x2

x6

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x144

x98

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x110

x114

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x142

xlowast97

xlowast101

xlowast105

xlowast109

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xlowast121

xlowast125

xlowast129

xlowast133

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xlowast141

xlowast99

xlowast103

xlowast107

xlowast111

xlowast115

xlowast119

xlowast123

xlowast127

xlowast131

xlowast135

xlowast139

xlowast143

xlowast49xlowast53

xlowast57

xlowast61

xlowast65

xlowast69

xlowast73

xlowast77

xlowast81

xlowast85

xlowast89

xlowast93

xlowast51xlowast55

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xlowast63

xlowast67

xlowast71

xlowast75

xlowast79

xlowast83

xlowast87

xlowast91

xlowast95

xlowast1

xlowast5

xlowast9

xlowast17

xlowast13

xlowast21

xlowast25

xlowast29

xlowast33

xlowast37

xlowast41

xlowast45

Reso

urce

blo

ck

01

98765432

xlowast3

xlowast7

xlowast11

xlowast19

xlowast15

xlowast23

xlowast27

xlowast31

xlowast35

xlowast39

xlowast43

xlowast471110

20 1 3 4 5 6 7 8 9Subframe

13121110

x4

x8

x12

x16

x20

x24

x28

x32

x36

x40

x44

x48

x2

x6

x10

x14

x18

x22

x26

x30

x34

x38

x42

x46

x52

x56

x60

x64

x68

x72

x76

x80

x84

x88

x92

x96

x50

x54

x58

x62

x66

x70

x74

x78

x82

x86

x90

x94

x100x104

x108

x112

x116

x120

x124

x128

x132

x136

x140

x144

x98

x102

x106

x110

x114

x118

x122

x126

x130

x134

x138

x142

xlowast97

xlowast101

xlowast105

xlowast109

xlowast113

xlowast117

xlowast121

xlowast125

xlowast129

xlowast133

xlowast137

xlowast141

xlowast99

xlowast103

xlowast107

xlowast111

xlowast115

xlowast119

xlowast123

xlowast127

xlowast131

xlowast135

xlowast139

xlowast143

Branch A1B3

(c) Data mapping at Tx1198601199011198613

Figure 10 Downlink data mapping of the LTE-A resource blocks used in the simulation

12 Mobile Information Systems

90

0005

001

0015

002

0025

003

With the proposed AE selection schemeWithout the proposed AE selection scheme

30 40 50 60 70 800

HPBW (deg)

Figure 11 Probability density of HPBW

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300

Case 2 PACE outdoor LOS 3kmhCase 3 PACE outdoor LOS 3kmh

Case 1 PACE outdoor LOS 3kmhCase 3 PACE outdoor NLOS 3kmhCase 2 PACE outdoor NLOS 3kmhCase 1 PACE outdoor NLOS 3kmh

EbN0 (dB)

Figure 12Users average BLERperformances based on the proposeddiversity system architecture

Figure 12 compares the usersrsquo average block error rate(BLER) performances obtained based on the proposeddiversity system architecture by using different transmissionschemes including Case 1 without STBC and TxBF Case2 with STBC only and Case 3 with STBC and TxBF viathe LTE pilot-assistant practical channel estimation (PACE)approach According to Figure 12 Case 1 has the worstperformance because there is no space-time coding and BFgain achieved About 17 dB of signal-to-noise ratio (SNR)gain at the target BLER can be achieved by Case 2 comparedwith Case 1 under the non-line-of-sight NLOS scenarioThere is about a 1 dB SNR gain that can be further achievedby employing the TxBF of Case 3 In addition the simulationresults under the LOS scenario are also provided as acomparison where almost 7 dB gain can be obtained whenthe LOS exists for those three cases

Next we simulate the BCE approaches and compare itsefficiency with the PACE based on the proposed diversitysystemarchitecture Figure 13 demonstrates the usersrsquo averageBLER via PACE and BCE approaches for three different

Table 1 Simulation parameters

Parameters ValueCarrier frequency 18GHzSystem bandwidth 20MHzFFT size 2048Number of data carriers 1200Number of samples in CP 144Subcarrier spacing 15 kHzBS antenna configuration(PM-MIMO) 1 MUX times 32 AE times 3 branches

BS AE spacing Half wavelengthUserrsquos antenna configuration 1 AE times 3 branches

Number of users 4 for 3D-BF diversity12 for 3D-BF multiplexing

Radius of userrsquos local area (119903UE) 15mAntenna type DipoleModulation QPSK

Number of scatterersOutdoor 4 clusters with 16scatterers per cluster (64 in

total)Scattering sphere radius 10mVelocity of UEs 3 60 and 120 kmhFading Flat

XPD value 58 dB and 97 dB for NLOSand LOS

Correlation 032 and 034 for NLOS andLOS

Rician 119870-factor 9 dB

userrsquos velocities including 3 60 and 120 kmh under theNLOS scenario An extension of other researches [14 31] isapplied to simulations of the polarized MIMO channel forwhich channel characteristics are also listed in Table 1 Wesee that the PACE performance decreases a lot due to highmobility at 60 and 120 kmh which indicates that the numberof pilots is not enough to compensate the channel correctlyin an environment with fast time-varying phase responseThe pilot density is 143 for PACE scheme and by consid-ering the trade-off regarding spectrum efficiency BCE thatrequires no or a minimal number of pilots might be betteremployed Figure 13 additionally shows the performances ofBCE schemes where performance is found that is not relevantto the userrsquos velocity Compared with the BCE reported byNgo and Larsson [29] our proposed BCE performance isbetter because the EVD is based on low correlated submatrixand has less complexity for doing the EVD based on asubmatrix with a smaller size Due to no pilot contaminationby BCE approach the proposed BCE outperforms PACEfor a velocity of 3 kmh when 119864

119887119873

0is less than 25 dB

However BCE has a higher complexity than PACE and itis condition constraint Again according to Figure 13 BCEperforms worse than PACE with a velocity of 3 kmh when119864119887119873

0is larger than 25 dB and the trend of error floor for

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

10minus1

100

UEs

aver

age B

LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia

International Journal of

Biomedical Imaging

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

12 Mobile Information Systems

90

0005

001

0015

002

0025

003

With the proposed AE selection schemeWithout the proposed AE selection scheme

30 40 50 60 70 800

HPBW (deg)

Figure 11 Probability density of HPBW

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300

Case 2 PACE outdoor LOS 3kmhCase 3 PACE outdoor LOS 3kmh

Case 1 PACE outdoor LOS 3kmhCase 3 PACE outdoor NLOS 3kmhCase 2 PACE outdoor NLOS 3kmhCase 1 PACE outdoor NLOS 3kmh

EbN0 (dB)

Figure 12Users average BLERperformances based on the proposeddiversity system architecture

Figure 12 compares the usersrsquo average block error rate(BLER) performances obtained based on the proposeddiversity system architecture by using different transmissionschemes including Case 1 without STBC and TxBF Case2 with STBC only and Case 3 with STBC and TxBF viathe LTE pilot-assistant practical channel estimation (PACE)approach According to Figure 12 Case 1 has the worstperformance because there is no space-time coding and BFgain achieved About 17 dB of signal-to-noise ratio (SNR)gain at the target BLER can be achieved by Case 2 comparedwith Case 1 under the non-line-of-sight NLOS scenarioThere is about a 1 dB SNR gain that can be further achievedby employing the TxBF of Case 3 In addition the simulationresults under the LOS scenario are also provided as acomparison where almost 7 dB gain can be obtained whenthe LOS exists for those three cases

Next we simulate the BCE approaches and compare itsefficiency with the PACE based on the proposed diversitysystemarchitecture Figure 13 demonstrates the usersrsquo averageBLER via PACE and BCE approaches for three different

Table 1 Simulation parameters

Parameters ValueCarrier frequency 18GHzSystem bandwidth 20MHzFFT size 2048Number of data carriers 1200Number of samples in CP 144Subcarrier spacing 15 kHzBS antenna configuration(PM-MIMO) 1 MUX times 32 AE times 3 branches

BS AE spacing Half wavelengthUserrsquos antenna configuration 1 AE times 3 branches

Number of users 4 for 3D-BF diversity12 for 3D-BF multiplexing

Radius of userrsquos local area (119903UE) 15mAntenna type DipoleModulation QPSK

Number of scatterersOutdoor 4 clusters with 16scatterers per cluster (64 in

total)Scattering sphere radius 10mVelocity of UEs 3 60 and 120 kmhFading Flat

XPD value 58 dB and 97 dB for NLOSand LOS

Correlation 032 and 034 for NLOS andLOS

Rician 119870-factor 9 dB

userrsquos velocities including 3 60 and 120 kmh under theNLOS scenario An extension of other researches [14 31] isapplied to simulations of the polarized MIMO channel forwhich channel characteristics are also listed in Table 1 Wesee that the PACE performance decreases a lot due to highmobility at 60 and 120 kmh which indicates that the numberof pilots is not enough to compensate the channel correctlyin an environment with fast time-varying phase responseThe pilot density is 143 for PACE scheme and by consid-ering the trade-off regarding spectrum efficiency BCE thatrequires no or a minimal number of pilots might be betteremployed Figure 13 additionally shows the performances ofBCE schemes where performance is found that is not relevantto the userrsquos velocity Compared with the BCE reported byNgo and Larsson [29] our proposed BCE performance isbetter because the EVD is based on low correlated submatrixand has less complexity for doing the EVD based on asubmatrix with a smaller size Due to no pilot contaminationby BCE approach the proposed BCE outperforms PACEfor a velocity of 3 kmh when 119864

119887119873

0is less than 25 dB

However BCE has a higher complexity than PACE and itis condition constraint Again according to Figure 13 BCEperforms worse than PACE with a velocity of 3 kmh when119864119887119873

0is larger than 25 dB and the trend of error floor for

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

10minus1

100

UEs

aver

age B

LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia

International Journal of

Biomedical Imaging

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mobile Information Systems 13

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 30 350

Proposed BCE outdoor NLOS 360120 kmhBCE by Ngo and Larsson outdoor NLOS 360120 kmhPACE outdoor NLOS 3kmhPACE outdoor NLOS 60kmhPACE outdoor NLOS 120 kmh

EbN0 (dB)

Figure 13 Usersrsquo average BLER performance by PACE and BCEunder an NLOS environment based on the proposed diversitysystem architecture

the proposed BCE occurs at 30 dB Figure 14 is given byconsidering the signal LOS component where performancecharacteristics observed are the same as Figure 13

0

Proposed BCE outdoor LOS 360120 kmhBCE by Ngo and Larsson outdoor LOS 360120 kmhPACE outdoor LOS 3kmhPACE outdoor LOS 60kmhPACE outdoor LOS 120 kmh

10 15 20 25 305

10minus2

10minus1

100

UEs

aver

age B

LER

EbN0 (dB)

Figure 14 Usersrsquo average BLER performance by PACE and BCEunder a LOS environment based on the proposed diversity systemarchitecture

At last we simulate the proposed multiplexing systemarchitecture via 3D beams where the channel matrix dedi-cated to a user is then given as

h119879119860119901119896(119905) = radic

120578

119878

119878

sum

119904=1

((

(

ℎ11987911986011198611198871198961198611

(119905) radic120583 sdot ℎ11987911986011198611198871198961198612

(119905) radic120583 sdot ℎ11987911986011198611198871198961198613

(119905)

ℎ11987911986021198611198871198961198611

(119905) radic120583 sdot ℎ11987911986021198611198871198961198612

(119905) radic120583 sdot ℎ11987911986021198611198871198961198613

(119905)

ℎ1198791198601199011198611198871198961198611

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198612

(119905) radic120583 sdot ℎ1198791198601199011198611198871198961198613

(119905)

))

)

(30)

According to channel matrix (30) the performance ofthe EVD-based BCE approach may decrease because theconstraint conditions of BCE are not preserved Howeverthe pilot contamination effect is reduced because there arefewer antennae using the same pilot positions For examplethere are 24 Tx antennae used in the proposed diversityscheme dedicated to a user where four antennae share thesame pilot positions In the proposed multiplexing schemeeight Tx antennae are dedicated to a user where two of themneed to share the same pilot position with other antennaeFigures 15 and 16 illustrate the userrsquos average BLER comparingthe multiplexing and diversity system architectures by 3Dbeams Note that the data rate of multiplexing is three timeshigher than the diversity scheme For PACE performancesthere is about 3 dB SNR gain at target BLER of 10minus2 (at3 kmh case) achieved by the diversity scheme comparedwith the multiplexing scheme mainly due to the gain ofQO-STBC However the gain is not significant because thepilot contamination effect is reduced when employing themultiplexing scheme with fewer antennae using the samepilot positions The BCE performance as discussed earliercannot be maintained with multiplexing since the constraintcondition of BCE is not fulfilled

6 Conclusions

M-MIMOhas been developed as a promising technology dueto several attractive features However there is less researchon M-MIMO systems with antenna polarization where theantenna polarization can copewith one of crucial constraintsa dimension in space to implement the M-MIMO In thispaper we propose a PM-MIMO array system with threeorthogonally colocated antenna branches equipped at eachAE of an M-MIMO system System architectures of diversityand multiplexing schemes realized by polarized 3D beamsare then proposed based on the proposed PM-MIMO arraysystem An array selection scheme for 3D-BF applicationsis additionally provided in this paper to efficiently optimizethe beam-width and to enhance system performance by theexploration of diversity and multiplexing gains In order toavoid pilot contamination in PM-MIMO we also propose aBCE approach to exploit pairwise orthogonality accordingto the particular characteristics of PM-MIMO systems Withthe proposed BCE approach 143 of spectral efficiencycan be increased while the gain in BLER performance isdependent on mobility compared with PACE Finally thesimulation results including the performances comparison

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia

International Journal of

Biomedical Imaging

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

14 Mobile Information Systems

5 10 15 20 25 30 350

10minus2

10minus1

100

UEs

aver

age B

LER

3D-BF diversity BCE outdoor NLOS 360kmh3D-BF multiplexing BCE outdoor NLOS 360kmh3D-BF diversity PACE outdoor NLOS 3kmh3D-BF multiplexing PACE outdoor NLOS 3kmh3D-BF diversity PACE outdoor NLOS 60kmh3D-BF multiplexing PACE outdoor NLOS 60kmh

EbN0 (dB)

Figure 15 Usersrsquo average BLER performance by the proposed diver-sity and multiplexing schemes via 3D beams under an NLOSenvironment

3D-BF diversity BCE outdoor LOS360kmh3D-BF multiplexing BCE outdoor LOS360kmh3D-BF diversity PACE outdoor LOS 3kmh3D-BF multiplexing PACE outdoor LOS 3kmh3D-BF diversity PACE outdoor LOS 60kmh3D-BF multiplexing PACE outdoor LOS 60kmh

10minus2

10minus1

100

UEs

aver

age B

LER

5 10 15 20 25 300EbN0 (dB)

Figure 16 Users average BLER performance by the proposeddiversity andmultiplexing schemes via 3D beams under a LOS envi-ronment

between PACE and BCE as well as diversity andmultiplexingschemes confirmed the validity of our proposals

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the MSIP (Ministry ofScience ICT and Future Planning) Korea under the ITRC(InformationTechnologyResearchCenter) Support Program(IITP-2015-H8501-15-1019) supervised by the IITP (Institute

for Information amp Communications Technology Promotion)and also was supported by ldquothe Fundamental Research Fundsfor the Central Universities (2015B30614)rdquo

References

[1] T L Marzetta ldquoNoncooperative cellular wireless with unlim-ited numbers of base station antennasrdquo IEEE Transactions onWireless Communications vol 9 no 11 pp 3590ndash3600 2010

[2] DW K Ng E S Lo and R Schober ldquoEnergy-efficient resourceallocation in OFDMA systems with large numbers of base sta-tion antennasrdquo IEEE Transactions onWireless Communicationsvol 11 no 9 pp 3292ndash3304 2012

[3] J Hoydis S Ten Brink andM Debbah ldquoMassive MIMO in theULDL of cellular networks how many antennas do we needrdquoIEEE Journal on Selected Areas in Communications vol 31 no2 pp 160ndash171 2013

[4] J G Andrews H Claussen M Dohler S Rangan and M CReed ldquoFemtocells past present and futurerdquo IEEE Journal onSelected Areas in Communications vol 30 no 3 pp 497ndash5082012

[5] H Q Ngo E G Larsson and T L Marzetta ldquoEnergy and spec-tral efficiency of very large multiuser MIMO systemsrdquo IEEETransactions on Communications vol 61 no 4 pp 1436ndash14492013

[6] A Fehske G Fettweis J Malmodin and G Biczok ldquoThe globalfootprint of mobile communications the ecological and eco-nomic perspectiverdquo IEEE Communications Magazine vol 49no 8 pp 55ndash62 2011

[7] T L Marzetta ldquoHow much training is required for multiuserMIMOrdquo in Proceedings of the 40th Asilomar Conference on Sig-nals Systems and Computers (ACSSC rsquo06) pp 359ndash363 PacificGrove Calif USA November 2006

[8] N Krishnan R D Yates and N B Mandayam ldquoUplink linearreceivers for multi-cell multiuser MIMO with pilot contamina-tion large system analysisrdquo IEEE Transactions onWireless Com-munications vol 13 no 8 pp 4360ndash4373 2014

[9] H Q Ngo T L Marzetta and E G Larsson ldquoAnalysis of thepilot contamination effect in very large multicell multiuserMIMO systems for physical channel modelsrdquo in Proceedings ofthe 36th IEEE International Conference onAcoustics Speech andSignal Processing (ICASSP rsquo11) pp 3464ndash3467 IEEE PragueCzech Republic May 2011

[10] S K Mohammed and E G Larsson ldquoSingle-user beamform-ing in large-scale MISO systems with per-antenna constant-envelope constraints the doughnut channelrdquo IEEE TransactionsonWireless Communications vol 11 no 11 pp 3992ndash4005 2012

[11] X Gao O Edfors F Rusek and F Tufvesson ldquoLinear pre-cod-ing performance in measured very-large MIMO channelsrdquo inProceedings of the IEEE Vehicular Technology Conference (VTCFall rsquo11) pp 1ndash5 San Francisco Calif USA September 2011

[12] S Payami and F Tufvesson ldquoChannel measurements and anal-ysis for very large array systems at 26 GHzrdquo in Proceedings ofthe 6th European Conference on Antennas and Propagation(EuCAP rsquo12) pp 433ndash437 IEEE Prague Czech Republic March2012

[13] J Hoydis C Hoek T Wild and S T Brink ldquoChannel mea-surements for large antenna arraysrdquo in Proceedings of the 9thInternational Symposium on Wireless Communication Systems(ISWCS rsquo12) pp 811ndash815 IEEE Paris France August 2012

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia

International Journal of

Biomedical Imaging

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mobile Information Systems 15

[14] X Su B Hui and K H Chang ldquo3-D MIMO channel mod-eling with beamforming analysis for dual-polarized antennasystemsrdquo in Proceedings of the IEEE 78th Vehicular TechnologyConference (VTCFall rsquo13) pp 1ndash5 LasVegasNevUSA Septem-ber 2013

[15] A S Y Poon and D N C Tse ldquoDegree-of-freedom gain fromusing polarimetric antenna elementsrdquo IEEE Transactions onInformation Theory vol 57 no 9 pp 5695ndash5709 2011

[16] X Su and K H Chang ldquoPolarized uniform linear array systembeam radiation pattern beamforming diversity order andchannel capacityrdquo International Journal of Antenna and Prop-agation vol 2015 Article ID 371236 9 pages 2015

[17] M-T Dao V-A Nguyen Y-T Im S-O Park and G Yoonldquo3D polarized channel modeling and performance comparisonof MIMO antenna configurations with different polarizationsrdquoIEEE Transactions on Antennas and Propagation vol 59 no 7pp 2672ndash2682 2011

[18] X Su and K Chang ldquoA comparative study on wireless backhaulsolutions for beyond 4G networkrdquo in Proceedings of the 27thInternational Conference on Information Networking (ICOINrsquo13) pp 505ndash510 IEEE Bangkok Thailand January 2013

[19] Y Li X D Ji D Liang and Y Li ldquoDynamic beamformingfor three-dimensional MIMO technique in LTE-advanced net-worksrdquo International Journal of Antennas and Propagation vol2013 Article ID 764507 8 pages 2013

[20] J Li U Park and S Kim ldquoAn efficient rate one STBCscheme with 3 transmit antennasrdquo in Proceedings of the Interna-tional Conference onWireless Communications Networking andMobile Computing (WiCOM rsquo08) pp 1ndash4 IEEE Dalian ChinaOctober 2008

[21] U Park S Kim K Lim and J Li ldquoA novel QO-STBC schemewith linear decoding for three and four transmit antennasrdquoIEEE Communications Letters vol 12 no 12 pp 868ndash870 2008

[22] W Liu ldquoAdaptive wideband beamforming with sensor delay-linesrdquo Signal Processing vol 89 no 5 pp 876ndash882 2009

[23] H F Yin D Gesbert M C Filippou and Y Z Liu ldquoDecon-taminating pilots in massive MIMO systemsrdquo in Proceedings ofthe IEEE International Conference onCommunications (ICC rsquo13)pp 3170ndash3175 IEEE Budapest Hungary June 2013

[24] L Lu G Y Li A L Swindlehurst A Ashikhmin and R ZhangldquoAn overview of massive MIMO benefits and challengesrdquo IEEEJournal on Selected Topics in Signal Processing vol 8 no 5 pp742ndash758 2014

[25] T E Bogale and L B Le ldquoPilot optimization and channel esti-mation formultiuser massiveMIMO systemsrdquo in Proceedings ofthe 48th Annual Conference on Information Sciences and Systems(CISS rsquo14) pp 1ndash6 Princeton NJ USA March 2014

[26] J Jose A Ashikhmin T L Marzetta and S Vishwanath ldquoPilotcontamination and precoding inmulti-cell TDD systemsrdquo IEEETransactions on Wireless Communications vol 10 no 8 pp2640ndash2651 2011

[27] E Beres and R Adve ldquoBlind channel estimation for orthogonalSTBC in MISO systemsrdquo IEEE Transactions on Vehicular Tech-nology vol 56 no 4 pp 2042ndash2050 2007

[28] B Muquet M de Courville and P Duhamel ldquoSubspace-basedblind and semi-blind channel estimation for OFDM systemsrdquoIEEE Transactions on Signal Processing vol 50 no 7 pp 1699ndash1712 2002

[29] H Q Ngo and E G Larsson ldquoEVD-based channel estimationin multicell multiuser MIMO systems with very large antennaarraysrdquo in Proceedings of the IEEE International Conference onAcoustics Speech and Signal Processing (ICASSP rsquo12) pp 3249ndash3252 IEEE Kyoto Japan March 2012

[30] MIMO transmission schemes for LTE and HSPA networks2009 httppersonsuniknoportenteachingUNIK4180Mate-riellMimo Transmission Schemes for LTE and HSPA Net-works June-2009pdf

[31] K Jeon X Su B Hui andK Chang ldquoPractical and simple wire-less channel models for use in multipolarized antenna systemsrdquoInternational Journal of Antennas and Propagation vol 2014Article ID 619304 10 pages 2014

[32] ETSI TS 136 211 v1020 (2011-06) ldquoLTE evolved universal ter-restrial radio access (E-UTRA) physical channels and modula-tionrdquo Technical Specification 2011

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia

International Journal of

Biomedical Imaging

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia

International Journal of

Biomedical Imaging

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ArtificialNeural Systems

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014