channel modelling –eti 085 antennas in real channels 8

Channel Modelling – ETI 085gLecture no: 88

AntennasAntennasMultiple antenna systemsp y

Fredrik TufvessonDepartment of Electrical and Information Technology

Lund University, [email protected]

2009-11-24 Fredrik Tufvesson - ETI 085 1

Antennas in real channels

• One important aspect is how the channel and antenna i t tinteract– The antenna pattern determines what the system sees

Delay spread and angular spread affected by the antenna pattern– Delay spread and angular spread affected by the antenna pattern

• The user may have a large influence on the behavior of theThe user may have a large influence on the behavior of the antenna– Change in antenna pattern– Change in efficiency – mismatch


What do we mean by real channels?

At the mobile side:• Mock-up terminals (handsetsMock up terminals (handsets,

lap-tops) with antenna and casing

• Near-by scattering environments y g– User influence– Indoor environments– In vehicles

At the base station side:• Type of installation – roof-top, yp p,

wall mount.• Obstacles or buildings near-by

or obstructive to the installation


Important antenna parameters

• DirectivitiyT t l i t i di ti d t t t l t itt d– Total power in a certain direction compared to total transmitted power

• EfficiencyradRη =

• Q-factorrad ohmic matchR R R

η =+ +

– Stored energy compared to dissipated energy• Mean effective gain

– Include influence of random channelInclude influence of random channel – Average received power compared to average received power by isotropic

antenna in real environmentP l i ti• Polarization

• Bandwidth


Example, antenna pattern

2090

elevation 1090

elevation

10

20

30

6090

120

150

180 0

5

10

30

6090

120

150

180 0

210

240270

300

330

180 0

210

240270

300

330

180 0

270 270

2060

90120

Azimuth 10

6090

120

Azimuth

10

20

30

6090

120

150

180 0

5

10

30

6090

120

150

180 0

210

240270

300

330

180 0

210

240270

300

330

180 0


3D antenna pattern

Gain

ElevationElevation

Azimuth


Influence of a user

Talk mode Data mode


Common antenna types

• Linear antennas (dipole, monopole)

• Helical antennas

• Microstrip antennas

• PIFA and RCDLA antennas


Linear antennas

• Hertzian dipole (short dipole)– Antenna pattern:

GainG, sin

– Gain

• λ/2 dipoleGmax 1.5

λ/2 dipole– Pattern

G, cos

2cos

i

– Gain

, sin

G 1 64Gmax 1.64


Helical antenna

• Combination of loop antenna and linear antenna– If dimensions much smaller than wavelength, behaves like linear

antenna– Bandwidth efficiency and radiation resistance increase withBandwidth, efficiency, and radiation resistance increase with

increasing h


Microstrip antennas

• Dielectric substrate with ground plane on one side, and t lli t h th thmetallic patch on the other

• Properties determined by Sh f t h i t b t l t– Shape of patch: size must be at least

– Dielectric properties of substrate

L 0.5substrate

Dielectric properties of substrate

• Advantages:substrate 0 / r

g• Small; can be manufactured cheaply• feedlines can be manufactured on same substrate as antenna

b i t t d i t th MS ith t ti ki t f th i• can be integrated into the MS, without sticking out from the casing

• Drawbacks:• Low bandwidth


Low bandwidth• Low efficiency

PIFA and RCDLA

• PIFA (Planar inverted F antenna)

• RCDLA (Radiation-coupled dual-L antenna


Mobile station antennas

Monopole Helix Patch


Impact of user on MS antenna

The efficiency depends on many parameters, but a very importantone is its environment. Below you can see differences in antennaefficiency for 42 test persons holding the mobile.

Up to around 10 pdB difference, depending on

personperson.


Multiband antennas

• For many applications, different wireless services need to b dbe covered

• Example: cellular handsetGSM 900– GSM 900

– GSM 1800– GSM 1900GSM 1900– Bluetooth


Base station antennas


Courtesey: Andrew Corp.


Base station antenna pattern affected by the mast (30 cm from antenna).

Narrowtmast

5 cmdiamdiam.mast

10 cmdiam.mast



Base station antenna pattern affected by a concrete foundation.


Multiple antenna systems

• What are MIMO systems?A MIMO system consists of several antenna elements, plus adaptive signal processing, at both transmitter and receiver, the combination of which exploits the spatial dimension of the mobile radio channelwhich exploits the spatial dimension of the mobile radio channel.

Transmitter ReceiverChannel

H1,1

H2 1A t 1

Antenna 1

Antenna 2H2,1

Hn,1TAntenna 1

Antenna 2

H

SignalprocessingData source

Signalprocessing Data sink

Antenna nT

Antenna nR

H1,nR

H2,nR

Hn,T nR


Benefits

• We can gain– higher capacity (bits/s/Hz) g p y ( )

spectrum is expensive; number of base stations limited– better transmission quality– increased coverage– improved user position estimation


Goals of MIMO

• increase power• beamformingArray gain • beamformingay ga

Diversity

• mitigate fading• space-time coding

Diversity

space time coding

S ti l lti l i • multiply data rates• spatially orthogonal channels

Spatial multiplexing


Goals of MIMO


Array gain• Directional antennas have gain• Received power:• Received power:

PR=GTGRPT(λ/4πd)2

• Mobile station moves → always follow user with main beam of yBS; point main beam of MS to BS

MS

BScell withomni-antenna

cell with directionalantenna


antenna

Diversity vs. beamformingDiversity: statistical independence of elementsBeamforming: coherence between elementsg


Spatial multiplexing

• Each MPC can carry independent data stream• Beamforming view:

– TX antenna “targets” energy onto one scatterer RX t i l f th t di ti– RX antenna receives only from that direction

• Capacity goes linearly with number of antennas


History

• Diversity:– Receive diversity: since 1940s– Transmit diversity: early 1990s

• Wittneben; Winters

– Space-time codes in late 1990s• Tarokh et al.; Alamouti

• Spatial multiplexing:• Spatial multiplexing:– Invented by Winters 1987– Theoretical treatment in mid-1990s

• Paulraj; Foschini&Gans; Telatar; Raleigh and Cioffi


Signal modelTransmitterPower P

Receiver

Antenna 1

H1,1

H2,1Hn,1T

Antenna 1Antenna 2

RXAntenna 2

TXRX

Antenna nR

H1,nR

H2,nR

Hn,T nR

Antenna nT

γ...SNR at each receiver branchH...transfer function


Narrow-band vs broad-band models• Narrow-band matrix channel H ....nR x nT

r = Hs + n

r [r r r ] T n 1 recei e signal ectorr = [r1 r2 ... rnR] T ..... nR x 1 receive signal vector

s = [s1 s2 ... snT] T.... nT x 1 transmit signal vector

n ... noise vector with E[n n H] = σn2 I nR

ideally H assumed i i d

B d b d h l t i t i f

ideally H assumed i.i.d.

• Broad-band channel matrix entries are frequency dependentH H ( )


H i,k = H i,k (ω)

Capacity formula

• Instantaneous channel characterized by matrix H• Shannon’s formula (for two-dimensional symbols):

HzsbitsHC //)||1(log 22 γ+=

• Foschini’s formula:

HzsbitsC H //detlog2 ⎟⎟⎞

⎜⎜⎛

⎥⎤

⎢⎡

+= HHI γ Hzsbitsn

CT

nR//detlog2 ⎟

⎟⎠

⎜⎜⎝

⎥⎦

⎢⎣

+ HHI


Capacity in realistic channels

Influence of various effects:• Correlation: LOS component, small angular spread• Keyholes: uncorrelated components, but low-rank transfer

matrix• Frequency selectivity: gives additional diversity• Limited number of effective scatterers


Channel knowledge is important for the system

• Channel knowledge at RX– unknown– known (estimated or perfect)

Channel knowledge at TX• Channel knowledge at TX– unknown (no channel state information, CSI)– average CSI knownaverage CSI known– instantaneous CSI known (estimated or perfect)

Different strategies for different combinations!


Mobile Feedback based CSI

• MS estimates hDLclosed loop control:feed h or w back

• Drawbacks:

• Feedback of DL channel parameters (hDL or wDL)

feed hDL or wDL back

• Drawbacks:– Reduces spectral

efficiency– Feedback errors (noise,

quantization)– Sensitivity to

UL

DL• high mobile speed• terminal implementation Estimate:

hDL


channel modelling –eti 085 antennas in real channels 8

Documents