Radio Resource Allocation in Multi-User Cooperative RelayingNetworks with Resource Block Pairing and Fairness Constraints

Muhammad Abrar • Xiang Gui • Amal Punchihewa

Received: 27 June 2012 / Accepted: 22 July 2013 / Published online: 8 August 2013

� Springer Science+Business Media New York 2013

Abstract In this paper we address the problem of radio

resource allocation in cooperative relaying networks. We

focus on the resource block and power allocations for

the downlink of OFDM-based relaying multi-user net-

work. The resource allocation is investigated for both

amplify and forward and decode and forward protocols

under the constraints of power, resource block pairing

and data rate fairness. To reduce complexity, the opti-

mization problem is solved in two steps. In the first step,

resource block pairing and allocation are conducted

jointly with equal transmission power for both the base

station and the relay. In the second step, transmission

power is further optimized to maximize the system

throughput. Our analysis is focused on the total achiev-

able system throughput and the achievable individual

throughput for each user.

Keywords Amplify and forward � Cooperative

networks � Decode and forward � Relay networks

1 Introduction

Cooperative relaying communication has been proposed to

meet the demand of higher transmission rate and reliability

of data transfer in mobile cellular networks which is

continuing to grow [1–5]. The relaying communication has

been proposed in the cellular networks to improve reli-

ability, enhance capacity, reduce total power consumption

and extend coverage area [6]. The idea of cooperative

communication in wireless environment is more attractive

due to the diverse quality of wireless channel and the

limited number of usable resources. With this cooperation,

users that experience a deep fade in their channel links can

utilize better channels provided by relays to improve their

quality of service. A segment of the cooperative network is

shown in Fig. 1. As the radio resources are limited in

wireless systems, efficient use of all these available

resources is necessary to achieve better performance. The

combination of cooperative relaying with multi-carrier

system provides promising design for the next generation

of wireless networks. In these systems, each sub-carrier

experiences an independent channel for different users.

Some of the sub-carriers may experience deep fading for

some users and hence are not suitable at that time instant

[7]. Therefore, allocation of sub-carriers to different users

according to channel conditions will improve system per-

formance in multipath frequency selective fading

environment.

Recently, several results on resource allocation in

cooperative relaying networks have been reported in the

literature [7–10]. In most of the literature, it is assumed

that the same sub-carrier is used in both the first and

the second hops of transmission [11–13]. But due to

independent channel fading on the same sub-carrier

over the two hops, the system performance may not be

optimal. The system performance can be enhanced

further by sub-carrier pairing in the two hops according

to their channel conditions [14]. In [14], sub-carrier

pairing based resource allocation for cooperative multi-

relay networks is addressed for the amplify and forward

(AF) protocol. In [9], the concept of sub-carrier pairing

in relay networks was introduced in the three-node

M. Abrar (&) � X. Gui � A. Punchihewa

School of Engineering and Advanced Technology, Massey

University, Palmerston North, New Zealand

e-mail: mabrarbari@gmail.com

123

Int J Wireless Inf Networks (2013) 20:346–354

DOI 10.1007/s10776-013-0215-7

network using the decode and forward (DF) protocol. In

[15], resource allocation with sub-carrier paring is

investigated under a joint sum-power constraint for both

AF and DF systems. Symbol error performance analysis

with sub-carrier pairing in OFDM relaying systems is

presented in [16]. In all of these papers, the network of

interest is a single source–destination pair with either

single relay or multiple relays. However, the problem of

sub-carrier pairing in multi-user network with data rate

fairness constraints is a non-trivial task. To the best of

the authors’ knowledge, this problem has not been well

explored in the literature yet. In this paper, we study

the problem of sub-carrier pairing, allocation and power

optimization in two-hop relay network with either AF

or DF protocols, respectively. The objective function is

to maximize the system throughput with sub-carrier

pairing under data rate fairness and total power

constraints.

The rest of the paper is organized as follows. Sec-

tion 2 describes the system model and basic assumptions.

Brief analysis of the system throughput and resource

block pairing is also introduced in this section. Problem

formulation and description is described in Sect. 3.

Furthermore, numerical results with simulation are

illustrated in Sect. 4. Finally, conclusion is provided in

Sect. 5.

2 System Model

In this paper we consider a two-hop multi-user relay-

assisted cooperative network that consist of M mobile

terminals (MTs), R relay terminals (RTs) and one base

station (BS). By considering multi-carrier transmission, it

is assumed that there are K resource blocks (RBs), each

consists of twelve consecutive sub-carriers as described

in the long term evolution (LTE) system [17]. In the rest

of the paper, the term resource block is used instead of a

sub-carrier. A downlink transmission is considered where

MTs receive information from the BS through the RTs.

The signal received at RT on the kth RB is forwarded to

MT over either the kth or the k0th RB, depending on the

RB pairing method as shown in Fig. 2. The frequency

selective channel is assumed as Rayleigh fading channel

and each sub-carrier in a single RB experiences the same

channel but different RBs experience different channel

conditions.

2.1 Instantaneous Channel Capacity and System

Throughput

For mathematical analysis, we assume that kth and k0thRBs are paired to be used in the first and second hop for

(a) (b)

Fig. 2 RB-pairing schemes: a Fixed order RB-pairing, b selective order RB-pairing

Hop-1 Hop-2BS

RTs MTs

Fig. 1 A segment of the cooperative relay network

Int J Wireless Inf Networks (2013) 20:346–354 347

123

mth MT, respectively. Let Pkb;m and Pk0

r;m be transmitted

powers of BS and rth RT for the mth MT on the RB-pair

(k,k0), respectively. hkb;r and hk

0

r;m are the channel coefficients

for the RB-pair (k,k0) from BS to the rth RT and the rth RT

to the mth MT, respectively. The respective noise powers at

rth RT and mth MT are denoted as r2r and r2

m. For the

analysis of throughput, we denote the instantaneous signal-

to-noise ratios (SNRs) at the mth MT using rth RT for AF

and DF protocols as ck;k0

r;m ðAFÞ and ck;k0

r;m ðDFÞ, respectively.

Following [3], these SNRs are given in (1) and (2), when

relay link is used only for transmission.

ck;k0

r;mðAFÞ ¼gk;k02

r;m Pkb;m hk

b;r

���

���

2

hk0r;m

���

���

2

r2m þ g

k;k02r;m hk0

r;m

���

���

2

r2r

ð1Þ

ck;k0

r;m ðDFÞ ¼ minPk

b;m hkb;r

���

���

2

r2r

;Pk0

r;m hk0

r;m

���

���

2

r2m

0

B@

1

CA ð2Þ

Here in (1) gk;k0

r;m is the scaling or amplification factor at the

rth RT on the RB-pair (k,k0) for the mth MT and is given

as

gk;k‘r;m ¼

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

Pk0

r;m

Pkb;m hk

b;r

���

���

2

þ r2r

vuuut ð3Þ

Equations (1) and (2) show the SNRs of respective

systems, when there is no direct transmission between BS

and MT. Using the standard Shannon capacity theorem

with zero SNR gap for simplicity, the instantaneous rate

achieved by the mth MT using the rth RT over the kth RB

for AF and DF is given as [6]:

rk;k0

r;m ðAF=DFÞ ¼ 1

2log2 ð 1þ ck;k0

r;m Þ ð4Þ

where ck;k0r;m is equal to either ck;k0

r;mðAFÞ or ck;k0r;mðDFÞ

depending on the system protocol. The factor � appears

here due to the half-duplex operation of relays. It

means relays transmit and receive in two different time

slots.

2.2 Resource Block Pairing

In relay communication, it is commonly assumed that

signal transmitted on the kth RB is amplified or deco-

ded at the relay and then retransmitted on the same kth

RB towards the destination. But due to independent

channel fading on the same RB over the two hops, the

system performance would not be optimal. The system

performance can be enhanced further by RB-pairing of

the two hops according to their channel conditions. In

this paper we investigate selective order RB-pairing

and compare its performance with fixed order RB-

pairing.

2.2.1 Fixed Order RB-Pairing

It is the most commonly assumed RB-pairing scheme,

where the kth RB in the first hop is paired with the same

kth RB in the second hop as shown in Fig. 2a. This

indicates that the signal transmitted by a source over one

RB in the first hop is forwarded by the relay on the same

RB in the second hop without considering channel

conditions.

2.2.2 Selective Order RB-Pairing

In selective order RB-pairing, the RBs in the first hop

are paired with RBs of the second hop according to

channel conditions. Each available RB with the highest

channel gain in the first hop is paired with the avail-

able RB with the highest channel gain in the second

hop for MT. The RB-pairing decision is made as

follow:

ðk; k0Þ ¼ arg½maxðCaÞ;maxðCbÞ� k 2 Ca; k0 2 Cb ð5Þ

where Ca and Cb are the set of RBs that are not paired

in the first and the second hops, respectively. After

pairing, k and k0 are removed from Ca and Cb,

respectively. This process is repeated until all the

available RBs in the first hop are paired with available

RBs in the second hop and then these paired RBs are

allocated to users. This process can easily be imple-

mented in single-user or multi-user networks when we

are not considering fairness in terms of data rate for

each user. But when we consider fairness constraints,

the RB-pairing and allocation should be carried out

jointly to guarantee the fairness among users. This is

the main constraint which we will include in our opti-

mization problem.

3 Problem Formulation and Description

First of all we define two binary variables dk;k0 and ak;k0m as

RB-pairing index and RB-allocation index, respectively.

dk;k0 ¼ 1 If the kth RB is paired with the k0th RB

0 Otherwise

�

348 Int J Wireless Inf Networks (2013) 20:346–354

123

ak;k0

m ¼ 1 If the RB pair k;k0ð Þ is allocated to the mth MT

0 Otherwise

�

ð6Þ

The total achieved network throughput (Rs) using (4)

and (6) over all RBs and MTs can be expressed as

Rs ¼XM

m¼1

XK

k¼1

XK

k0¼1

1

2log2 1þ dk;k0ak;k0

m c;k;k0

r;m

� �

ð7Þ

3.1 Joint RB and Power Allocation Based

on RB-Pairing

Considering joint RB and power allocation with RB-pair-

ing, an optimization problem is formulated in this sub-

section. The main goal of this optimization problem is to

maximize the overall system throughput, which is given by

(7).

MaximizeXM

m¼1

XK

k¼1

XK

k0¼1

1

2log2 1þ dk;k0ak;k0

m ck;k0

r;m

� �

ð8Þ

Subject to the following constrains

C1 RB-pairing constraint: The RB-pairing constraint is

that each RB in the first hop can be paired with only

one RB in the second hop

XK

k¼1

dk;k0 ¼ 1 8 k0 andXK

k0¼1

dk;k0 ¼ 1 8 k ð8aÞ

C2 RB-allocation constraint: The RB-allocation

constraint is that each RB-pair can be used only by

one MT to avoid intra-cell interference

XM

m¼1

ak;k0

m � 1 ; ak;k0

m 2 f0; 1g 8 k; 8 k0 ð8bÞ

C3 Data-rate constraint: This constraint ensures that each

MT meets the minimum data rate requirement. Let

rm,min is the minimum rate requirement (MRR) for

each MT

XK

k¼1

XK

k0¼1

dk;k0ak;k0

m rk;k0

r;m � rm;min 8m ð8cÞ

C4 Power constraint: The total maximum network

transmission power is limited by total power

constraint:

dk;k0 ðPkb;r þ Pk0

r;mÞ � PT 8 k; 8 k0 ð8dÞ

where PT is the total transmission power for two-hop

transmission over RB-pair (k,k0).

The variables in the optimization problem defined by

(8) are: RB-pairing, RB allocation, and power alloca-

tion. The solution to (8) is based on the joint optimi-

zation of these variables subject to the constraints listed

in (8a)–(8d). This type of joint optimization problem

may be solved by centralized control system, which will

require separate channel for information exchange.

However, the solution of such an optimization problem

is NP hard due to extremely high computation com-

plexity [18].

3.2 Two-Step RB and Power Allocation Based on RB-

Pairing

Since the optimization problem in (8) is combinatorial

due to both discrete (RB pairing and allocation) and

continuous (power allocation) variables, the computa-

tional complexity is high to find an optimal solution.

In order to reduce complexity, two-step resource allo-

cation is proposed in this paper. In the first step, a RB-

pairing and allocation scheme is proposed. At the end

of first step, all of the integer variables are fixed. In

the second step, power allocation is carried out to

optimize the objective function under total power

limitations.

3.2.1 RB Pairing and Allocation Scheme

In the RB-pairing and allocation scheme, we optimize

the overall system throughput by ensuring fairness

among all users. The optimization problem as descri-

bed in (8) is developed and the RB allocation is made

in the following three sub-steps at equal power

allocation.

S-1 In the first sub-step, user selection is made. The

priority of users is set with respect to their

received SNRs in the first hop. In each round,

the MT with the highest received SNR in the first

hop is selected to start the RB-pairing process.

This step is repeated before S-2 or S-3 for all RBs,

so that each user can get a fair chance to use its

best channel and it ensures that the best channel is

used by the best user, based on received SNR in

the first hop.

S-2 RB-pairing along with allocation to MTs is done in

this sub-step. The RB with the best channel gain in

the first hop is paired with the RB with the best

Int J Wireless Inf Networks (2013) 20:346–354 349

123

channel gain in the second hop for the selected MT

in S-1 and is allocated to this selected MT. The

minimum rate satisfaction is achieved in this step.

This process continues till either all the MTs

achieved their minimum rate requirement or all the

RB-pairs are allocated. Each RB-pair is allocated

to only one MT to avoid intra-cell interference.

This step provides guarantee that any user with

higher data rate requirement or with the best

channel could not use all the resources at the

expense of other users.

S-3 If the minimum rate requirements for all MTs

have been achieved and still there are un-

allocated RBs, then this sub-step allows these

RBs to be used by the best user to maximize the

system throughput. This step continues along with

the S-1 until all RBs are allocated. This step aims

to make sure that only the user with the best

channel gains uses these un-allocated RBs in each

round.

3.2.2 Power Allocation

After the first step of RB-pairing and allocation satisfying

the individual MRR, the power is allocated to BS and RT

by optimizing the objective function given in (8) with the

total power constraint given in (8d). The optimization

problem can be re-written as

MaximizeXM

m¼1

XK

k¼1

XK

k0¼1

1

2log2 ð1þ dk;k0ak;k0

m ck;k‘r;mÞ ð9Þ

Subject to : dk;k0 ðPkb;r þ Pk0

r;mÞ � PT 8 k ; 8 k0 ð9aÞ

where only the transmission powers are variables because

binary variables dk;k0 and ak;k0m are already determined in the

first step.

The optimal power allocation can be obtained by using

Lagrange multiplier techniques. For AF, using (1) in (9),

we have

Maximize

XM

m¼1

1

2log2 1þ

Pkb;rc

mb;rPr;mcm

r;m

Pkb;rc

mb;r þ Pk0

r;mcmr;m þ 1

!

ð10Þ

Subject to : dk;k0 ðPkb;r þ Pk0

r;mÞ � PT 8 k; 8 k0 ð10aÞ

where cmb;r ¼ hk

b;r

���

���

2

=r2r ; cm

r;m ¼ hk0r;m

���

���

2

=r2m; r2

m ¼ r2r ¼

r2 and dk;k0 ¼ ak;k0m ¼ 1 for all paired and allocated

RBs. It is obvious that (11) is maximized when the term

Pkb;rc

mb;rPk0

r;mcmr;m

Pkb;r

cmb;rþPk0

r;mcmr;m þ 1

is maximized. To simplify the problem we

assume high SNR regime which is a commonly used

assumption in the literature [6, 8]. In this way ‘‘1’’ in the

denominator can be removed and problem becomes as

shown in (11).

MaximizePk

b;rcmb;rP

k0r;mcm

r;m

Pkb;rc

mb;r þ Pk0

r;mcmr;m

Subject to : constraint 10að Þð11Þ

By applying Lagrange multiplier techniques on (1) with

total power constraints, the optimal power allocations are

obtained as in [15] for AF.

Pkb;r ¼

�cmr;m þ

ffiffiffiffiffiffiffiffiffiffiffiffiffiffifficm

b;r:cmr;m

p

cmb;r cm

r;m

:PT if cmb;r 6¼ cm

r;m

PT=2 if cmb;r¼ cm

r;m

8

><

>:

9

>=

>;

; Pk0

r;m

¼cm

b;r �ffiffiffiffiffiffiffiffiffiffiffiffiffiffifficm

b;r:cmr;m

p

cmb;r � cm

r;m

� PT if cmb;r 6¼ cm

r;m

PT=2 if cmb;r¼ cm

r;m

8

><

>:

9

>=

>;

ð12Þ

Similarly it is straightforward for DF that maximization

is achieved when the SNRs of both hops are equal [15], i.e.,

Pkb;rc

mb;r ¼ Pk0

r;mcmr;m. The optimal power allocation for DF

is therefore given as

Pkb;r ¼

cmr;m

cmb;r þ cm

r;m

:PT ; Pk0

r;m ¼cm

b;r

cmb;r þ cm

r;m

:PT ; ð13Þ

3.2.3 Resource Allocation Algorithm

Taking into account the objective function and its con-

straints, the process of RB and power allocation based on

RB-pairing is depicted in Algorithm 1.

350 Int J Wireless Inf Networks (2013) 20:346–354

123

4 Performance Evaluation

In this section, we present and discuss some simulation

results to evaluate the performance of the RB-pairing based

resource allocation. In this simulation we assume that relay

is located in between BS and each MT and there is no

direct link available for transmission. The number of MTs

is 5 and RBs is 14. The MRR = 1 Mb/s for each mobile.

Only one RT is allowed to cooperate with one MT. The

line-of-sight (LOS) path loss model is used for BS-RT link

as we assume that relays are in LOS of BS which has

directional antennas for transmission. The non line-of-sight

Path loss model is used for RT-MT links. Both path loss

models follow those defined for the Urban Micro envi-

ronment for the evaluation of 4G mobile wireless systems

[19]. No shadowing loss is considered here. We use

MATLAB environment for all simulations. The proposed

algorithm has been evaluated in terms of total achievable

system throughput and achievable individual throughput of

each MT.

Figure 3 shows the individual throughputs of each MT

for AF and DF systems, respectively. It is observed that

Int J Wireless Inf Networks (2013) 20:346–354 351

123

when there is no pairing and no fairness, some MTs get

much higher throughputs than others. Even worse, there are

some MTs could not meet their MRR in both systems. By

applying pairing, we observed that throughput has been

significantly increased. The pairing and fairness technique

not only provide fairness among users in term of MRR but

also provide significant increase in individual data rate.

Figure 4 shows the total achieved throughput for AF and

DF systems with and without RB-pairing against increasing

number of RBs. In both AF and DF systems MRR con-

straint is implemented. The better results are achieved with

RB-pairing than without RB-pairing. It is also noticeable

that the gain in performance with RB-pairing increases

with the number of available RBs. Because the more RBs,

the more flexibility that the system has in exploiting the

channel diversity gains. To achieve more reliable results,

the performance is obtained as the average of 100 random

channel realizations by setting received SNR per hop to

20 dB.

Figure 5 presents the result of power optimization in

both AF and DF systems. The overall system throughput is

observed at different total transmission powers. A signifi-

cant throughput performance gain has been observed by

optimizing the power on all RBs over equal power on all

RBs. It is clear that selective order RB-pairing itself pro-

vide higher data rates than conventional fixed order RB-

pairing, but more data rate gain be achieved by optimizing

the power for all allocated RB-pairs.

5 Conclusions

In this paper, the problem of resource allocation in multi-

user relaying networks with resource block pairing has

been addressed for both AF and DF protocols. A joint

1 2 3 4 50

0.5

1

1.5

2

2.5

3

3.5

4

MTs ID

Thr

ough

put(

Mb/

S)

Number of RBs=14

MRR

No Pairing, No Fairness

Pairing, No Fairness No Pairing, Fairness

Pairing, Fairness

1 2 3 4 50

0.5

1

1.5

2

2.5

3

3.5

4

MTs ID

Thr

ough

put(

Mb/

S)

Number of RBs=14

MRR

No Pairing, No Fairness

Pairing, No Fairness No Pairing, Fairness

Pairing, Fairness

(a) (b)

Fig. 3 Achieved individual throughput of each MT: a AF, b DF

2 8 14 20 26 320

2

4

6

8

10

12

14

16

18

20

Number of RBs

Sys

tem

Thr

ough

put(

Mb/

S)

AF w/o Pairing

AF with PairingDF w/o Pairing

DF with Pairing

Number of MTs = 5

Fig. 4 Achieved system throughput versus number of RBs

1 2 3 4 5 6 7 8 9 105

6

7

8

9

10

11

12

13

14

Total Transmitted Power (W)

Sys

tem

Thr

ough

put(

Mb/

S)

EPA, DF w/o Pairing

OPA, DF w/o PairingEPA, DF with Pairing

OPA, DF with Pairing

EPA, AF w/o Pairing

OPA, AF w/o PairingEPA, AF with Pairing

OPA, AF with Pairing

DF

AF

Number of MTs=5Number of RBs=14

Fig. 5 Achieved system throughput versus total transmitted power

352 Int J Wireless Inf Networks (2013) 20:346–354

123

optimization problem with an objective function of maxi-

mizing system throughput has been formulated under total

transmission power, resource block pairing and allocation

and data rate fairness constraints. To reduce complexity,

two-step resource allocation is proposed in this paper. In

the first step, a joint RB pairing and allocation is proposed

and in the second step, power allocation is carried out to

optimize the objective function under total power limita-

tions. Simulation results show the effectiveness of selective

order resource block pairing over fixed order resource

block pairing.

References

1. J. N. Laneman, et al., Cooperative diversity in wireless networks:

Efficient protocols and outage behavior, IEEE Transactions on

Information Theory, Vol. 50, pp. 3062–3080, 2004.

2. A. Nosratinia, et al., Cooperative communication in wireless

networks, IEEE Communications Magazine, Vol. 42, pp. 74–80,

2004.

3. K. J. R. Liu, Cooperative Communications and Networking:

Cambridge University Press, Cambridge University PressNew

York, 2009.

4. K. Loa, et al., IMT-advanced relay standards [WiMAX/LTE

Update], IEEE Communications Magazine, Vol. 48, pp. 40–48,

2010.

5. A. Sendonaris, et al., User cooperation diversity. Part I. System

description, IEEE Transactions on Communications, Vol. 51,

pp. 1927–1938, 2003.

6. Y. W. Hong, et al., Cooperative communications in resource-

constrained wireless networks, IEEE Signal Processing Maga-

zine, Vol. 24, pp. 47–57, 2007.

7. W. Lingfan and R. D. Murch, Cooperation strategies and resource

allocations in multiuser OFDMA systems, IEEE Transactions on

Vehicular Technology, Vol. 58, pp. 2331–2342, 2009.

8. S. Sadr, et al., Radio resource allocation algorithms for the

downlink of multiuser OFDM communication systems, IEEE

Communications Surveys & Tutorials, Vol. 11, pp. 92–106, 2009.

9. Y. Wang, et al., Power allocation and subcarrier pairing algorithm

for regenerative OFDM relay system, IEEE 65th Vehicular Tech-

nology Conference, 2007. VTC2007-Spring. pp. 2727–2731, 2007.

10. K. T. Phan, et al., Power allocation in wireless multi-user relay

networks, IEEE Transactions on Wireless Communications, Vol.

8, pp. 2535–2545, 2009.

11. S. Kuang-Yu, et al., Resource allocation and partner selection for

cooperative multicarrier systems, IEEE Transactions on Vehicu-

lar Technology, Vol. 60, pp. 3228–3240, 2011.

12. M. Abrar, G. Xiang, P. Amal, Sub-carrier allocation for downlink

multi-user OFDM cooperative cellular networks, 6th Interna-

tional Conference on Broadband and Biomedical Communica-

tions (IB2Com), 2011, pp. 63–67, 2011.

13. A. Agustin, et al., Protocols and resource allocation for the two-

way relay channel with half-duplex terminals, IEEE International

Conference on Communications, 2009. ICC ‘09, pp. 1–5, 2009.

14. D. Wenbing, et al., Subcarrier-pair based resource allocation for

cooperative multi-relay OFDM systems, IEEE Transactions on

Wireless Communications, Vol. 9, pp. 1640–1649, 2010.

15. L. Yong, et al., Subcarrier pairing for amplify-and-forward and

decode-and-forward OFDM relay links, IEEE Communications

Letters, Vol. 13, pp. 209–211, 2009.

16. C. Shaohua, et al., Symbol error performance analysis of OFDM

relaying system with subcarrier mapping scheme, IEEE Com-

munications Letters, Vol. 14, pp. 638–640, 2010.

17. 3rd Generation Partnership Project, Technical Specification

Group RadioAccess Network; Physical Layer Aspect; 3GPP TS

36.201 version 10.0.0.

18. S. Bond and L. Vandenberghe, Convex optimization, Cambridge

University PressCambridge, 2004.

19. Guidelines for Evaluation of Radio Interface Technologies for

IMT-Advanced, 2008. http://www.itu.int/pub/R-REP-M.2135-

2008/en. Accessed 20 June 2012

Author Biographies

Muhammad Abrar received

the B.Sc. degree in Electrical

Engineering with First Class

from the University of Engi-

neering and Technology (UET)

Taxila, Pakistan, in 2000 and

the M.Sc. degree from UET

Lahore, Pakistan in 2007. He is

currently pursuing his Ph.D.

studies at the School of Engi-

neering and Advanced Tech-

nology (SEAT), Massey

University, New Zealand. His

current research interests are

wireless networks including

MIMO, Relay networks and cooperative communications.

Xiang Gui received his B.S.

and M.S. degrees from Shang-

hai Jiao Tong University, China,

in 1991 and 1994, respectively,

and the Ph.D. degree from the

University of Hong Kong in

1998, all in electrical engineer-

ing. In 1994, he was an Assis-

tant Lecturer in the Department

of Electrical Engineering,

Shanghai Jiao Tong University,

China. From 1998 to 2003, he

worked at Nanyang Technolog-

ical University, Singapore, first

as a Research Fellow then as an

Assistant Professor. In 2003, he joined Massey University as a Lec-

turer at the Institute of Information Sciences and Technology. Cur-

rently he is a Senior Lecturer with the School of Engineering and

Advanced Technology at Massey University, Palmerston North, New

Zealand. His research interests include wireless and mobile commu-

nications & applications, multicarrier, MIMO & spread spectrum

systems, and cooperative communication networks. Dr. Gui is a

Senior Member of IEEE and serves as a regular reviewer for a number

of quality professional journals and international conferences. He is

also a founding member of the Joint Chapter in Communications,

Signal Processing and Information Theory established in 2009 under

the IEEE New Zealand Central Section.

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123

Amal Punchihewa obtained a

Bachelor of Engineering, spe-

cializing in Electronics and

Telecommunication Engineer-

ing, from the University of

Moratuwa in Katubedda, Sri

Lanka, with honours in 1986. In

1991 he completed a Master of

Electronics Engineering at the

Technical University of Eind-

hoven, The Netherlands, focus-

ing on digital video signal

processing. Amal has worked as

an engineer in both academia

and industry over the past

24 years, starting as a computer engineer in 1986. After 3 years he

moved to the broadcast industry, working as a research engineer for

the national television broadcaster in Sri Lanka. In 1994 he became a

senior lecturer at the University of Moratuwa, before migrating to

New Zealand in 2002, where he joined Massey University in Pal-

merston North. His Ph.D. was on framework for rapid evaluation of

image and video compression artefacts objectively. He is a senior

lecturer and his current research interests are objective assessment of

compression artefacts and image processing for surveillance, multi-

media communication and care of the elderly. Amal is a fellow of the

Institution of Engineering and Technology, a member of Institution of

Professional Engineers New Zealand, and a life member of the Sri

Lanka Association for Advancement of Science. In 2000 he was

awarded the Wimalasurendra award in recognition of the contribution

he made to the broadcasting development by the Institution of

Engineers Sri Lanka.

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