resource allocation in full duplex heterogeneous networks ...resource allocation in full duplex...

Resource Allocation in Full Duplex Heterogeneous

Networks with eICIC

Jun Zhang and Hui Tian State Key Laboratory of Networking and Switching Technology,

Beijing University of Posts and Telecommunication, Beijing 100876, China

Email: [email protected]; [email protected]

Abstract— In this paper, we consider a two-tier heterogeneous

Orthogonal Frequency Division Multiple Access (OFDMA)

network which consists of one Full Duplex (FD) macrocell and

several FD femtocells. Enhanced Inter-Cell Interference

Coordination (eICIC) by means of Almost Blank Subframe

(ABS) is considered to reduce the cross-tier interference. We

formulate a resource allocation problem to maximize the sum-

rate of the network by jointly allocating subcarrier and power

among user equipments (UEs). The problem is solved by a sub-

optimal algorithm, which greedily allocates subcarriers based on

necessary conditions of the optimization problem and then

distributes power of Base Stations (BSs) and UEs by Iterative

Water Filling (IWF) procedure. Simulation results reveal that

the proposed subcarrier and power allocation algorithm improve

the throughput over the Time Division Duplexing (TDD) Half

Duplex (HD) system and the FD system with a round-robin

scheduler. The FD gain of the macrocell can achieve 45% when

the ABS scheme is applied, while the FD technique almost

doubles the throughput of the femtocells.

Index Terms—Full duplex, OFDMA, resource allocation,

subcarrier and power allocation

I. INTRODUCTION

Recent studies have shown that next generation

wireless communication systems are expecting to

accommodate greatly growing mobile traffic [1], [2].

However, traditional bi-directional communication is

achieved by either frequency division duplexing (FDD)

or Time Division Duplexing (TDD) [3], which suffers

from low spectrum efficiency compared with Full Duplex

(FD) technology. FD technology enables a node to

transmit and receive simultaneously on the same

frequency band and thus potentially doubles the spectral

efficiency. Recent progress in signal processing can

efficiently cancel the Self-Interference (SI) in FD and

brings in-band wireless FD into reality [4], [5]. FD

technology, as a candidate of future 5th Generation (5G)

radio access technology, has received lots of attention

from the academic and industrial community [6]-[10].

Manuscript received January 11, 2016; revised June 21, 2016.

This work was supported by the National Science and Technology Major Project under Grant No. 2015ZX03001025-002 and Huawei

Company. Corresponding author email: [email protected].

doi:10.12720/jcm.11.6.550-557

The main difficulty of FD technology to realize the

almost doubled spectral efficiency lies in the strong SI

imposed by the signal leakage from the transmitter

antennas of a FD node to its own receiver antennas. The

techniques to handle SI cancellation can be generally

categorized into three different types, namely the antenna

cancellation, the analog cancellation and the digital

cancellation. Antenna cancellation technique relies on

directional isolation, absorptive shielding and cross-

polarization to isolate the transmit and receive antennas

[11], [12]. Analog cancellation methods generate a

delayed and attenuated copy of the transmit signal, and

then subtract it from receive signal [13], [14]. After

digitalize the analog receive signal, digital cancellation

can clean out residual SI caused by non-linear RF chains

[14], [15]. The three cancellation techniques are usually

combined to obtain high SI cancellation gain. Recently SI

cancellation value up to 110dB has been reported [13].

The FD Medium Access Control (MAC) layer design

has been investigated in cellular networks. A single small

cell was considered in [16]-[19]. A hybrid scheduler that

adapts to FD or Half Duplex (HD) operation according to

the link channel and interference conditions was proposed

in [16], [18]. Sub-optimal joint subcarrier and power

allocation algorithms were considered to maximize the

system throughput in [17], [19]. On the other hand, the

multi-cell scenarios were also investigated in [7], [20]

and [21]. The performance of FD communication was

evaluated in a dense small cell scenario and 30-40%

mean throughput gain over HD transmission was

observed [7]. A heuristic greedy scheduling algorithm

and power allocation based on geometric programming

were proposed in [20] and 60% FD gain was show in

outdoor pico cell deployment. A utility function defined

by the sum of the logarithm of users’ data rates was

maximized to maintain fairness among FD users [21].

However, few literatures addressed the resource

allocation in FD heterogeneous networks. The network

throughput of a heterogeneous network was derived by

accounting the node density, and SI cancellation value

using the stochastic geometry [22]. The closed-form

approximations for sum ergodic capacity have been

derived in interference coordinated heterogeneous

networks but Equal Power Allocation (EPA) was

assumed [23]. The FD gain achieved by joint subcarrier

Journal of Communications Vol. 11, No. 6, June 2016

©2016 Journal of Communications 550

and power allocation in heterogeneous networks has not

been exploited, which is the aim of this paper.

The 3GPP has proposed the enhanced Inter-Cell

Interference Coordination (eICIC) to alleviate the cross-

tier interference in co-channel deployed heterogeneous

networks in Release 10 [24]. One of the features is the

almost blank subframe (ABS). The strong interfering

nodes are muted in both data and control channels and

only reference signal is transmitted during the ABS

subframe. This allows the victim nodes to schedule their

users without cross-tier interference. The ABS scheme is

also considered in this paper.

In this paper, we consider a joint subcarrier and power

allocation problem in a FD heterogeneous network. A

sub-optimal algorithm is proposed by firstly assigning

subcarrier to uplink and downlink users while considering

the users’ minimum data rate constraints. Secondly the

power is distributed by Iterative Water Filling (IWF)

algorithm. Furthermore, we investigate the effect of

interference coordination scheme on the FD gain. We

compare the performance of the proposed algorithm with

that of a TDD HD system as well as a FD system with

Round-Robin (FD-RR) scheduler. The simulation results

show that the proposed resource allocation scheme can

improve the throughput over TDD HD and FD-RR

systems. The FD gain is enhanced when the interference

coordination scheme is applied in the heterogeneous

network.

The rest of this paper is organized as follows. Section 2

provides the system model. In Section 3, we formulate

the joint subcarrier and power allocation problem. A sub-

optimal algorithm is proposed in Section 4 followed by

simulation results in Section 5. Finally, Section 6

concludes this paper.

II. SYSTEM MODEL

We consider a heterogeneous network consists of one

macrocell and a set of femtocells. The heterogeneous

network operates in a single-input and single-output

(SISO) orthogonal frequency division multiple access

(OFDMA) system with N subcarriers. A FD base station

(BS) is located at the center of the macrocell and serves

randomly distributed HD uplink and downlink macrocell

users (MUE). The number of the uplink and downlink

MUE are U and D , respectively. The radius of the

macrocell is MR . The femtocells are co-channel deployed

with the macrocell. Each femtocell communicates with its

femtocell user (FUE) in its Close Subscriber Group (CSG)

within a radius FR . For simplicity, we assume there is

only one FUE in every femtocell. Both the femtocell and

the FUE operate in FD mode. Let us denote the set of

uplink MUEs, downlink MUEs and subcarriers as UL , DL and respectively. Since we assume there is a

single FUE per femtocell, we use to denote the set of

femtocells or the set of FUEs without causing much

ambiguity. In the considered heterogeneous network, the

femtocells are strong disrupters and should apply ABS to

avoid causing severe cross-tier interference to the MUEs

in their proximity. The ABS ratio is denoted as .

III. PROBLEM FORMULATION

In this section, we present the data rates in normal

subframes and ABS subframes. Then, we formulate a

joint subcarrier and power allocation problem to

maximize the sum rate of the heterogeneous network. We

also derive a criterion to assign subcarriers based on

Karush-Kuhn-Tucker (KKT) conditions.

A. Date Rates in Normal Subframes

The macrocell BS simultaneously receives signal from

one of its uplink user and transmits signal to one of its

downlink user. At the same time, the co-channel

femtocells generate interference to the macrocell in

normal subframes. The macrocell schedules the thi uplink

MUE, and thk downlink MUE on the thn subcarrier. The

data rate of the thi uplink MUE on the thn subcarrier is

given as

, ,,UL

, 2

,

0,

1

MU UL

i n i nM

ik n MB

k n

FB FU nMB

SI

PR log

P

H

I IC

(1)

where 1

, ,

FB

FB l n l n

l

I P H and 2

, ,

FU

FU l n l n

l

I P H are the

interference generated by FD femtocell BSs and FUEs,

respectively. ,

MU

i nP , ,

MB

k nP , ,

FB

l nP and ,

FU

l nP denote the

transmit power of the thi uplink MUE, the macrocell BS,

the thl femtocell BS and the thl FUE on the thn subcarrier,

respectively. ,

UL

i nH , 1

,l nH and 2

,l nH are the channel from

the thi uplink MUE to the macro BS, the thl femtocell BS

to the macro BS and the thl FUE to the macro BS,

respectively. MB

SIC denotes the SI cancelation value at the

macro BS [16]. 0, n is the noise power on the thn

subcarrier.

The data rate of the thk downlink MUE on the thn

subcarrier is given as

, ,,DL

, 2 ' '

, , 0,

(1 )

MB DL

k n k nM

ki n MU

i n ki n FB FU n

PR log

P H I I

H (2)

where ' 3

, ,

FB

FB l n l n

l

I P H and ' 4

, ,

FU

FU l n l n

l

I P H are the

interference generated by the FD femtocell and FUEs,

respectively. ,

DL

k nH , ,ki nH , 3

,l nH and 4

,l nH denote the

channel from the macrocell BS to the thk downlink MUE,

the thi uplink MUE to the thk downlink MUE, the thl

femtocell BS to the thk downlink MUE and the thl FUE

to the thk downlink MUE, respectively.



The data rate at the thl femtocell BS in the uplink

transmission on the thn subcarrier is given as

, ,,UL

, 2

, 7

, , 0,

1

FU UL

l n l nF

l n FB

l n MB

FB FU k n k n nFB

SI

P HR log

PJ HJ P

C

(3)

where 5

, ,

,

FB

FB k n k n

k k l

J P H and 6

, ,

,

FU

FU k n k n

k k l

J P H are

the interference generated by co-channel femtocell BSs

and FUEs, respectively. ,

UL

l nH , 5

,k nH , 6

,k nH and 7

,k nH are

the channel from the thl FUE to the thl femtocell BS, the

thk femtocell BS to the thl femtocell BS, the thk FUE to

the thl femtocell BS and the macrocell BS to the thl

femtocell BS, respectively. FB

SIC is the SI cancelation

value at the femtocell BS.

The data rate at the thl femtocell BS in the downlink

transmission on the thn subcarrier is given as

, ,,DL

, 2

, ' ' 10

, , 0,

1

FB DL

l n l nF

l n FU

l n MB

FB FU k n k n nFU

SI

P HR log

PJ J P

CH

(4)

where ' 8

, ,

,

FB

FB k n k n

k k l

J P H and ' 9

, ,

,

FU

FU k n k n

k k l

J P H are

the interference from co-channel femtocell BSs and FUEs

to the thl FUE, respectively. ,

DL

l nH , 8

,k nH , 9

,k nH and 10

,k nH

the channel from the thl femtocell BS to the thl FUE, the

thk femtocell BS to the thl FUE, the thk FUE to the thl

FUE and the macrocell BS to the thl FUE, respectively.

FU

SIC is SI cancelation value at the FUE.

B. Data Rates in ABS Subframes

In ABS subframe, the femtocells are muted with data

transmission. As a consequence, there is no cross-tier

interference from the femtocell tier to the macrocell. The

data rates at the uplink and downlink channels by

scheduling the thi uplink MUE and thk downlink MUE

on the thn subcarrier are given as

, ,,DL

, 2

, , 0,

1

MB DL

k n k nM

ki n MU

i n ki n n

PD log

P

H

H (5)

, ,,UL

, 2

, 0,

1

MU UL

i n i nM

ik n MB MB

k n SI n

HPD log

P C

(6)

C. Joint Subcarrier and Power Allocation Problem

Formulation

Given the ABS ratio , the sum rate of the thi uplink

MUE and thk downlink MUE on the thn subcarrier is

given as

,UL ,DL ,UL ,DL

, , , , ,1 M M M M M

ik n ik n ki n ik n ki nC R R D D (7)

The sum rate of the heterogeneous network on the thn

subcarrier is given by

,DL ,UL ,DL ,UL

, , , , ,1

M M F F

ik n ki n ik n l n l n

l

C R R R R

,DL ,UL

, , M M

ki n ik nD D (8)

In this paper, our goal is to maximize the sum rate of

the heterogeneous network by optimizing scheduling and

power allocation scheme. We formulate the problem as

,max

UL DL

nik ik n

i kn

a CMB MU

A,P ,P

(9)

s.t.

C1: ,

1

DL

NMB

k n MB

n k

P P

C2: ,

1

N

MU

i n U

n

P P

C3: ,

,

1

,

UL

NM UL UL UL

ik n t

n k

C R i

C4: ,

,

1

,?

DL

NM DL DL DL

ik n t

n i

C R k

C5: 1

UL DL

nik

i k

a

C6: 0,1 , , nika n

, UL DLi k

C7: , 0, , MB UL

k nP k n

C8: , 0, , MU DL

i nP i n

where constraints C1 and C2 limit the transmit power of

each femtocell BS and UE to be below MBP and UP ,

respectively. C3 and C4 set the QoS requirement UL

tR

and DL

tR to ensure the minimum date rates of the uplink

and downlink MUEs, respectively. We assume the

minimum date rate constraints are feasible for every user.

C5 and C6 are imposed to guarantee that each subcarrier

can only allocated to at most one uplink and downlink

MUE pair. C7 and C8 represent the non-negative power

constraint of the transmit power on each subcarrier. The

variable matrices A , MBP and MU

P are obtained by

stacking all nika , ,

MB

k nP and ,

MU

i nP , respectively. Note that

we assume the femtocell BSs and FUEs employ EPA

among the subcarriers for simplicity (i.e., , FU Ul n

PP and

, FB FBl n

PP , l , where is the cardinality of the

sets and FBP is the maximum transmit power of FBSs).

Due to the exclusive nature of subcarrier assignment,

the optimization problem (9) is an integer optimization

problem. Although the problem can be optimally solved



via exhaustive search, the complexity involved increases

exponentially as the number of users and subcarriers

increase. Therefore, we relax the constraints C6 as

0,1nika . The relaxed problem is still not a convex

problem, because it is not jointly concave in their solution

space. However, any optimal solution still satisfies the

KKT conditions, so we can obtain a criterion to schedule

UE pairs based on the KKT condition. In particular, we

have the following proposition.

Proposition 1: To maximize the objective function (9),

the subcarrier n is allocated to the UE pair with thi uplink

and thk downlink users selected by

* *

,,

, arg max

UL DL

ik ni k

i k C (10)

Proof: The Lagrangian function of the optimization

problem (9) is defined by

MB MUA,P ,P ,μ,λ,β (11)

, 0 ,

1 1

UL DL DL

N NMB

nik ik n k n MB

n ni k k

a C P P

,

, ,

1 1

UL UL UL

N NMU M UL UL

i i n U i ik n t

n ni i k

P P C R

,

,

1

1

DL DL UL DL

NM DL DL

k ik n t n nik

n nk i i k

C R a

where μ , λ and β are the stacked Lagrange multipliers.

Deriving partial derivative of with respect to nika , we

get

,

0, 0

0, 0

nik

ik n n

niknik

if

aif

aC

a (12)

From (12), if subcarrier n is allocated to the UE pair

with thi and thk users (i.e. 0nika ), the UE pair has the

largest ,ik nC among other UE pairs, which implies (10).

IV. PROPOSED RESOURCE ALLOCATION ALGORITHM

In this section, we design a heuristic algorithm based

on Proposition 1. The proposed algorithm greedily

allocates the subcarriers to the UE pairs maximizing the

increase of the sum rate of the UE pair in step 1. The UE

pairs are selected from the uplink and downlink UEs pairs,

whose minimum data rates are not satisfied. In order to

eliminate the dependence on transmit power of the MUEs

and MBS, the uplink and downlink dates are calculated

by assuming the EPA of the transmit powers. In step 2,

the residual subcarrier is allocated to UE pairs, whose

minimum data rate requirement is not satisfied only in the

uplink or the downlink, to further increase the sum

throughput. Then given the subcarrier allocation, the

power of the MBS and MUEs are distributed using IWF

algorithm in step 3[25].

Let us denote UL

iS and DL

kS as the subcarrier assigned

to the thi uplink MUE and thk downlink MUE,

respectively. Let denote the unassigned subcarriers.

We use UL and DL to denote the uplink and downlink user whose minimum data rates are not satisfied, respectively. The data rates of the communication links

are obtained under EPA, i.e. , MB MB

k n

PP ,

, MU Ui n

PP ,

, FB FBl n

PP and

, FU Ul n

PP . Data rate of the

thi uplink

MUE and thk downlink MUE is given as

, ,UL ,UL

, ,1

ULi

M UL UL M M

i i ik n ik n

n S

R S R D (13)

, ,DL ,DL

, ,1

DLk

M DL DL M M

k k ki n ki n

n S

R S R D (14)

The sum data rate of the femtocell tier on the

subcarrier set UL DL

i kS S is given as

,DL ,UL

, ,1

UL DLi k

F UL DL F F

i k l n l n

ln S S

R S S R R (15)

The detailed algorithm is given in Table I. Note that

there are two IWF algorithms, namely IWF1 and IWF2,

in step 3, since the interference from femtocells is

different in normal subframes and ABS subframes. In

Table I, denotes the empty set and ,0x max x .

TABLE I: PROPOSED RESOURCE ALLOCATION ALGORITHM

Data: Channel gains: 1 2 3

, , , , , , , ,, , , , , , ,UL DL UL DLi n k n ki n l n l n l n l n l nH H H H H H HH .

4 5 6 7 8 9 10

, , , , , , , , , , , , ,l n k n k n k n k n k n k nH H H H H H H

Maximum power constraints: MBP , FBP and UP .

Initialization: UL

iS , DL

kS , ,

UL UL , DL DL , 0n

Step 1: Subcarrier allocation for UL

tR and DL

tR

While UL and DL and

1) 1 n n , UL UL

i iS S n , DL DL

k kS S n .

2) ik

, , M UL UL M DL DL F UL DLi i k k i kR S R S R S S

, , M UL UL M DL DL F UL DLi i k k i kR S R S R S S

3) * *

,

, arg max

UL DL

iki k

i k

4) * * * * * *1,?,? UL UL DL DL

ni k i i k ka S S n S S n

5) Update * *

,M UL UL

i iR S and * *

,M DL DL

k kR S

6) If * *

, M UL UL ULti i

R S R , */UL UL i end if

7) If * *

, M DL DL DLtk k

R S R , */DL DL k end if

8) / n

End loop

Step 2: Residual subcarrier allocation

Residual subcarrier allocation is almost the same as step 1. The only difference is that line 3 must be replaced by:

If UL and DL



9) * *

,

, arg max

UL DL

iki k

i k

Else if UL and DL

10) * *

,

, arg max

UL DL

iki k

i k

Else

11) * *

,

, arg max

UL DL

iki k

i k

End if

Step 3: Iterative water-filling algorithm

In normal subframes, perform IWF1 algorithm.

In ABS subframes, perform IWF2 algorithm.

IWF1: For iteration 1: max _iterationm

For UL DLi

If ULi

12) , 0,

,

,

MB MB

k n SI FB FU nMU

i n i ULi n

P C I IP

H,

s.t. ,

ULi

NMU

i n U

n S

P P

Else

13)

' '

, , 0,

,

, ,

MU

k n ik n FB FU nMB

i n i MB DLk n k n

P H I

H

IP

P,

s.t. ,

DLi

DLN

i MBMBi n

n S

S PP

N

End if End loop End loop

IWF2: For iteration 1: max _iterationm

For UL DLi

If ULi

14)

,

0,

,

,

MBk n

nMBMU SI

i n i ULi n

P

CP

H,

s.t. ,

ULi

NMU

i n U

n S

P P

Else

15) , , 0,

,

, ,

MU

k n ik n nMB

i n i MB DLk n k n

P HP

P H

s.t. ,

DLi

DLN

i MBMBi n

n S

S PP

N

End if End loop End loop

Result: subcarrier indicator A , power allocation MBP and MU

P .

V. SIMULATION RESULTS

In this section, we present a simulation analysis

comparing the throughput of the proposed joint FD

scheduling and power allocation algorithm (denoted as

FD-P) with that of a FD-RR system and a TDD HD

system in the same simulation setting. We evaluate the

throughput of TDD HD by firstly assuming the all

subcarriers are dedicated to uplink or downlink

communication respectively. Then the throughput of

TDD HD system is obtained by halving the sum of the

uplink and the downlink throughput. The throughput of

TDD HD system is equivalent to that of a TDD HD

system with symmetric uplink and downlink time slot

configuration. The SI cancellation values are the same for

the MBS, the FBSs and FUEs.

We adopt 3GPP LTE specifications for heterogeneous

network simulation [26]-[28]. The channel in femtocells

is assumed to experience the path loss model for indoor

hotzone. In particular, path losses for line-of-sight (LOS)

and non-line-of-sight (NLOS) are given with the

probability as

LOS

1, 0.018

0.018 / 0.027 ,0.018 0.037

0.5, 0.037

d

P exp d d

d

where d is in kilometers. The penetration loss between

MBS and FBSs and between FBSs is set to 10dB . All the

channels are subject to independent identical distributed

(i.i.d.) Rayleigh fading coefficients with unit mean.

Without loss of generality, we assume identical power

constraints for the MUEs and FUEs. All the results are

obtained over 500 drops. Detailed simulation parameters

are shown in the Table II.

TABLE II: S

Parameter Setting

MR 500m

FR 50m

4

,U D 10,10

System bandwidth 10MHz

Number of subcarriers 50

MBP 43dBm

FBP 20dBm

UP 23dBm

Thermal Noise Density -174dB/Hz

Path loss for Macrocell 128.1+37.6log10(d) Path loss for femtocell LOS: 89.5 +16.9log10(d)

NLOS: 147.4 + 43.4log10(d)

,UL DL

t tR R 1 Mbps, 2 Mbps

TABLE III: THE TOTAL FD GAIN OF THE HETEROGENEOUS NETWORK

SI cancellati

on value

110dB 100dB 90dB 80dB 70dB

FD-P 69% 66% 65% 62% 56%

FD-RR 58% 57% 55% 53% 45%

The total FD gain is defined by the average increase of

sum rate of the heterogeneous network over TDD HD in

all subframes. Table III depicts the total FD gain of the

heterogeneous networks at various SI cancellation values

when 0.1 . It shows that both the FD-P and FD-RR

scheme cannot double the sum rate and can achieve 69%

and 58% FD gain at SI cancellation value 110dB and

100dB, respectively. The FD-P scheme obtained about

11% more total FD gain over the FD-RR scheme.

However, since the interference conditions are different

between the macroll and the femtocells and between ABS



IMULATION ARAMETERSP

subframes and normal subframes, it’s beneficial to

inspect the FD gain of the macrocell and the femtocells,

respectively.

The sum rate of the macrocell of the FD-RR and FD-P

scheme in normal subframes are shown in Fig. 1, where

SI x dB means the SI cancellation value is x dB .

When FD-RR scheme is employed, there is no gain of the

sum rate of macrocell compared with the TDD HD

systems. This is due to there are strong Inter-User

Interference (IUI) since RR scheduler is used. What’s

more, the co-channel femtocells cause severe interference

to the downlink reception of the MUEs in their vicinity.

The FD-P scheme schedules UE pairs with small IUI and

can obtain FD gain. However, under the best practical SI

cancelation value of 110dB, FD-P achieves about 21%

gain. In order to further exploit FD gain, eICIC schemes

such as ABS should be employed to reduce the cross-tier

interference.

0 100 200 300 400 500 6000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Sum rate of the macrocll (Mbps)

CD

F

SI=110dB

SI=100dB

SI=70dB

TDD HD

FD-P

FD-RR

Fig. 1. The sum rate of the macrocell in FD-P and FD-RR in normal

subframes

100 200 300 400 500 600 7000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Sum rate of the Macrocell (Mbps)

CD

F

SI=110dB

SI=100dB

SI=70dB

TDD HD

FD-P

FD-RR

Fig. 2. The sum rate of the macrocell in FD-P and FD-RR in ABS

subframes

In ABS subframes, the sum rate of the macrocell is

shown in Fig. 2. The figure confirms that the FD-RR

cannot provide any FD gain due to the strong IUI. The

FD-RR only provides comparable performance with the

TDD HD system on 110dB SI cancelation value.

However, notable FD gain is achieved by FD-P scheme.

The FD gains are 46% and 32% at SI cancelation value of

110dB and 100dB, respectively. The FD gains of the FD-

P scheme are much higher than that of Fig. 1. This shows

that FD systems are more prone to cross-tier interference

and eICIC is required to mitigate severe cross-tier

interference in heterogeneous deployment.

The total FD gain of the macrocell in the FD-P scheme

is defined by the average increase of the sum rate of the

macrocell over TDD HD mode in all the subframes. The

total FD gain under various ABS ratios is indicated in Fig.

3. It is illustrated that the total FD gain of the FD-P

scheme increases with ABS ratio. However, the total FD

gain increases faster with the ABS ratio at higher SI

cancellation value. The reason is that the FD gain of the

FD-P scheme at high SI cancellation values(e.g. 110dB)

in ABS subframes is much bigger than that at low SI

cancellation value(e.g. 70dB) as depicted by Fig. 2. The

total FD gain can achieve about 45% at SI cancellation

value of 110dB.

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.95

10

15

20

25

30

35

40

45

50

ABS Ratio

Tota

l F

D G

ain

(%

)

SI=110dB

SI=100dB

SI=70dB

Fig. 3. Total FD gain of the marocell of the FD-P scheme

0 100 200 300 400 500 600 700 800 900 10000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Sum rate of femtocells (Mbps)

CD

F

FD-P,SI=110dB

FD-P,SI=70dB

TDD HD

FD-RR,SI=110dB

FD-RR,SI=70dB

Fig. 4. The sum rate of the femtocells in normal subframes

Fig. 4 depicts the sum rate of the femtocells in normal

subframes when the macrocell employs the FD-P and

FD-RR scheme. It is seen that both the schemes achieve

almost doubled gain of sum rate of femtocells over the

TDD HD scheme. There are two reasons: First, the link

distances in the femtocells are short, so the signal is much

stronger than the interfrerence and SI. Secondly, since

both the femtocell BSs and FUEs operated in FD mode,

there are no IUI. This observation also shows that



femtocell is suitable for deployment of FD technology.

What’s more, the FD-P degrades a small amount of the

sum rate of the femtocells, since the FD-P scheme

generates more cross-tier interference to the femtocells

compared with the FD-RR scheme.

VI. CONCLUSION

In this paper, we have formulated a joint subcarrier and

power allocation problem in the heterogeneous network.

To solve the problem, we proposed a three-step algorithm,

which greedily allocates the subcarriers to satisfy the

minimum data rate requirement of the MUEs under EPA

and then perform IWF procedure to distributed power

under individual BSs’ and UEs’ power constraints. We

considered the eICIC by means of ABS to alleviate cross-

tier interference. Performance evaluation demonstrates

that the proposed scheme can exploit FD gain in the

heterogeneous network. What’s more, a high FD gain up

to 45% can be obtained on ABS subframes, which proves

that FD technology is prone to cross-tier interference.

ACKNOWLEDGMENT

This work was supported by National Science and

Technology Major Project under grant No.

2015ZX03001025-002 and Huawei Company.

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Jun Zhang received the B.S. degree from

Hubei University of Arts and Science,

Xiangfan, China, in 2007 and the M.S.

degree from Shanghai Normal University,

Shanghai, China, in 2010. Currently, he is

a Ph.D. candidate in Beijing University of

Posts and Telecommunications (BUPT),

China. His research interests mainly

include heterogeneous networks,

interference cancelation, radio resource management and

stochastic geometry.

Hui Tian received the M.S. and Ph.D.

degrees both from Beijing University of

Posts and Telecommunications (BUPT)

of China in 1992 and 2003, respectively.

Now she is a professor in BUPT and the

director of the Media Access Lab. (MAT)

of Wireless Technology Innovation

Institute (WTI). Her research interests

mainly include LTE and 4G system design, MAC protocols,

resource scheduling, ad hoc and sensor networks, radio resource

management.



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