Random-Based Fair Allocation in Multi-Relay ... - IEEE Xplore

First International Workshop on the Performance Enhancements in MIMO-OFDM Systems

Random-Based Fair Allocation in Multi-Relay Cooperative OFDM System Ibrahim Y. Abualhaol, Youssef Iraqi

Khalifa University of Science, Technology, and Research Sharjah, United Arab Emirates Email: {ibrahimee, iraqi}@ieee.org

Abstract-In this paper, a novel Multi-relay Adaptive Random Selection (MARS) strategy in a dual-hop multi-relay OFDM sys­ tem is proposed. In this strategy, the relays cooperate according to contribution factors suggested by each relay. The selection of the OFDM sub-channels is based on uniform random distribution where the thresholds of the uniform random variable are asso­ ciated with the contribution factors. This approach guarantees fairness in allocating the resources in each relay. The approach is compared with static allocation of the OFDM sub-channels. The MARS strategy is tested in a multi relay system over flat and selective Rayleigh fading channels. Simulation results show the superiority of the proposed scheme in improving the OFDM system performance in terms of BER. The performance is achieved by creating a virtual diversity by randomizing the allocation where no channel information is required.

I.

INTRODUCTION

Early consideration of relay-assisted communication sys­ tems appeared in the literature in [1] where the simplest relay channel model is comprised of three nodes: a source (8) that transmits information, a destination (D) that receives information, and a relay (R) that both receives and transmits information to enhance the communication between the source and the destination. Extended models with multiple relays have been examined in [2] and [3]. The cooperative relaying has been proved to have better system performance compared to the direct link without relay. The improvement in the system performance is maximized by optimizing the selection of relays and allocating the resources [4]-[7]. Orthogonal Frequency Division Multiplexing (OFDM) is a major technology in 4G because of the ability to mitigate the inter-symbol interference and the frequency selectivity in wireless channels. The joint optimization of resources (i.e., power and sub-channels) offers superior gain to the system performance [8]. Moreover, combining the relay-based coop­ erative system with OFDM system promises further gain in the system performance in terms of BER [9]. Recently, the authors in [10] considered an Amplify and Forward (AF) cooperative two-hop multi-relay OFDM system, where they optimally and jointly allocate power, sub-channels and relay nodes with the objective of maximizing the trans­ mission rate. The authors in [11] formulated the joint relay selection and sub-channel matching problem as an integer programming problem. This approach is complex and assumes full knowledge of channel information.

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In this paper we address the joint fair allocation of relays and OFDM sub-channels to improve the performance in terms of BER assuming no channel information. Fairness is achieved by considering contribution factors given by the relays. The contribution factors give an idea about how much the relays are willing to cooperate. The approach is to introduce additional diversity through random allocation of the resources. We pro­ pose a novel Multi-relay Adaptive Random Selection (MARS) strategy in a dual-hop multi-relay OFDM system. This strategy is assessed over flat and selective Rayleigh fading channels. The results showed significant improvement. The remainder of this paper is organized as follows. Section II introduces the system and channel model under considera­ tion. Section ill presents the multi-relay random selection al­ gorithm. The performance of the proposed scheme is assessed using Monte Carlo simulation in Section IV. Finally, the paper is concluded in section V. II.

SYSTEM AND CHANNEL MODEL

Consider a cooperative multi-relay wireless communication system as in Fig. 1, where 8 is the source communicating with the destination D indirectly through N relays which help in improving the communication link between 8 and D. Assume that 8 is transmitting a signal x(t), which has an average power normalized to one (i.e., E[x2(t)] 1), then the received signal at relay Ri can be written as =

(1)

where as R. is the fading amplitude of the channel between the source's and the relay �. nSR.(t) is an Additive White Gaussian Noise (AWGN) signal with one sided power spectral density (PSD) given as NSR.' The received signal is multiplied by the gain Gi of the no�-regenerative relay Ri and then retransmitted to the destination D. The AF technique is known to have less latency and hardware complexity compared with detect and forward (DF) technique. The received signal at D from relay Ri can then be written as

where aR.D is the fading amplitude of the channel between relay Ri �d the destination D. nR.D (t) is an AWGN signal with one sided PSD NRi D . The coinbination of the received

596

signals at the destination D from relays Rl , R2 , ..., RN can therefore be written as

N

rD(t) =

2:: rRiD(t)

(3)

i=l

The instantaneous signal-to-noise ratio (SNR) at D, i(t), can be written as

i(t) = E[x2(t)]

x

[I:�1 G/iRD aSR] 2 . 2 E [[I:�1 GiaRiDnSRi(t) +nRiD(t) ] 11 t-

"

(4)

Fig. 1.

Assuming that nSR(t) and nRD(t) are identical indepen­ ' dent AWGN with on� sided PSD No for all i = 1,2, . . . , N. Then (4) becomes

III.

Two-hop multi-relay cooperative OFDM system.

MULTI-RELAY ADAPTI VE RANDOM SELECTION STRATEGY

(5)

where E[x2(t)]!No is the average SNR of an AWGN channel and Gi is the gain associated with relay Ri . If we considered the use of K OFDM sub-channels, then the instantaneous SNR associated with each sub-channel k E {I, 2, ... , K} can be given from (5) as

(6)

It is important to mention that some relays may not con­ tribute in the achieved SNR that is associated with certain sub-channel. Fairness is an important requirement in any allocation tech­ nique and to formulate our problem we propose the following assignment variable which takes the values 0 or 1; where 1 means that the relay Ri contributes in improving (t) of the kth sub-channel and 0 otherwise. Then, equation (6) becomes

A�k)

i(k)

In this section we propose an enhanced fair random allo­ cation algorithm for multi-relay OFDM system. As it is clear from (7) the received SNR associated with the kth OFDM sub­ channel (i.e., i (t » ) is affected by the fading from source to relay and from relay to destination. In our proposed algorithm we do not require any channel information. Each relay Ri specifies a contribution factor Ci that gives an idea about how much this relay is willing to cooperate. In addition, we assume that each OFDM sub-channel will be relayed using only one relay. This means that = 1 for all values of k.

(k)

I:�1 A�k)

One direct fair allocation solution (given that Ci are the only known information) is to statically allocate a number of sub­ channels to each of the relays proportional to the probability cj• This sub-channel allocation will be static p( i) = ) throughout the lifetime of the transmission. We will call this allocation: Multi-relay Static Random Selection (MSRS). This strategy guarantees fair allocation of the relays resources.

2:{:

Our proposed allocation strategy is to use the same proba­ bility p( i) and allocate the resources randomly as given in the following Multi-relay Adaptive Random Selection (MARS) Algorithm 1. In this case, the sub-channels allocation will be changed for every OFDM-symbol. The MARS algorithm starts by collecting the contribution factors Ci for every relay. Then, computing the selection probability p( i) = Cj for each relay. The selection

2:f�:

A�k)

The goal is to find the values of for i = 1,2, ..., N and k = 1,2, ... , K that achieve fair allocation of the OFDM sub-channels.

probabilities are then associated with equivalent regions as shown in Fig. 2. A uniform random variable U(O,l) is generated for every OFDM sub-channel k and the result is used to locate the selection region where the value of the uniform random variable result is located. After that, the assignment variable is set to one and all = 0 where v =I- j.

597

Ajk)

A�k)

Algorithm 1 Multi-relay Adaptive Random Selection for i 1 to N do Receive contribution factors Ci for relay Ri. end for for i 1 to N do Compute the selection probability p( i) cj end for Generate selection regions as shown in Fig. 2 for each relay Ri. for k 1 to K do • Generate uniform random variable for sub-channel k. • Locate the selection region j where the value of the uniform random variable result is located. • Set the corresponding value in the assignment variable to one: 1. • Set 0 where v =I- j. end for =

=

=

2:£:

•

=

A(k) A�k)

=

=

in the multiuser diversity. Whereas in the case of selective fading the multiuser diversity is almost the same using MSRS or MARS allocations. Fig. 4 investigates the performance of MARS allocation and compares it with MSRS allocation for five relays with contribution factors C1 C2 C3 C4 C5 1. Again, the performance of MARS is superior in flat fading. However, in this case, using more relays results in an improvement of channel diversity which is indicated by higher performance in selective fading for high SNR values. In the second simulation scenario, we investigated different contribution factors for the relays. Fig.S depicts a comparison between MARS and MSRS al­ locations for the contribution factors C1 1, C2 2, C3 4 over flat and selective Rayleigh fading channels. The superi­ ority of MARS over MSRS in the case of flat fading channels is obvious. Considering five relays with contribution factors C1 1, C2 2, C3 4, C4 8, C5 10, it is clear that MARS has a very good improvement in the performance over both types of fading as shown in Fig. 6. This improvement comes from the combined spatial diversity of relays and the random channel selection. =

=

=

=

=

=

=

=

=

=

p(1)

p(2)

peN)

p(3)

=

=

=

10' ������������r;==C::: � :::= =':=?====il

o

Fig. 2.

IV.

- One Relay Flat . - . - . One Relay Selective � 3 Relays-MSRS-Flat � 3 Relays-MARS-Flat - • - 3 Relays-MSRS-Seleclive - � - 3 Relays-MARS-Seleclive

MARS selection probability regions

SIMULATION RESULTS

In this simulation, a two-hop multi-relay communication system is assumed as shown in Fig. 1. The fading am­ plitudes aSR' and aRD for i 1,2, . . . , N are assumed to be identic�1 indepe�dent Rayleigh random variables with E[las RI2] E[laRDI2] 1. Each relay Ri is assumed to have a �ontribution factor Ci. The OFDM system parameters that have been used in the simulations are given in Table I. The simulations are conducted using two types of fading. The first type is the flat fading where the Rayleigh fading amplitude remains constant over the entire OFDM-symbol. The second type is the selective fading where each sub-channel experiences different fading amplitude. In our simulation, to avoid unfair comparison, all relays Rl , R2 , . . . , RN relay signal with unity gain (i.e., Vi, Gi 1) which will eliminate the possibility of having enhancement due to relay gains. We investigated two simulation scenarios. In the first sce­ nario, an equal contribution factor is assumed for the relays. Assuming three relays cooperative system with contribution factors C1 C2 C3 1. The comparison between MSRS and MARS over flat and selective Rayleigh fading channels is shown in Fig. 3. The improvement in the system performance in terms of BER is very obvious in flat fading case and there is minor improvement in the case of selective fading. It is clear from Fig. 3 that the performances of MARS and MSRS are better than single relay. The MARS allocation in flat fading improves the system performance thanks to the improvement =

=

=

10 -20':----,':--':----,':----,':-----:0,=---:"=- 2 --:',-:4 ----:'6,::-----:',::8 ---:02 SNR[dBJ

Fig. 3. BER performance comparison of MSRS and MARS in three relays system with C1 = C2 = C3 = lover selective and flat Rayleigh fading channels.

=

=

=

V. CONCLUSION In this paper, a Multi-relay Adaptive Random Selection (MARS) algorithm for cooperative multi relay OFDM system

=

598

TABLE I SYSTEM PARAMETERS Bandwidth (BW) No. of sub-channels (K) sub-channel separation (,6,.f) Symbol time (T.) Cyclic prefix time (Tcyd Modulation

20 MHz 64 3 12.5 KHz 3.2 J.i,s 0.8 J.i,s BPSK

' , o ���������������==�����==� -- One Relay Flat

f ,i �������������� r=������==� -- One Relay Flat

. - . _.

. - . - . One Relay Selective

One Relay Selective

---+- 5 Relays-MSRS-Flat ---0-- 5 Relays-MARS-Flat - • - 5 Relays-MSRS-Selective - � - 5 Relays-MARS-Selective

5 Relays-MSRS-Flal ---0-- 5 Relays-MARS-Flal - • - 5 Relays-MSRS-Seleclive - � - 5 Relays-MARS-Seleclive ---+-

,o·, '-----'----':--'--....J o m a M . g w

---'---'-----"-' -----': --'-:- ' ----'0 10 -20"----'-------'--" '2--'- 4 ' -----6:-0 8 2 SNR(dBJ

SNR(dBJ

Fig. 4. BER performance comparison of MSRS and MARS in five relays system with Cl = C2 = C3 = C4 = C5 = lover selective and flat Rayleigh fading channels.

Fig. 6. BER performance comparison of MSRS and MARS in five relays system with Cl = 1, C2 = 2, C3 = 4, C4 = 8, C5 = 10 over selective and flat Rayleigh fading channels.

f ,i c--,-�-,--,,--,---,--,_r==�����==�

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-- One Relay Flat

. - . - . One Relay Selective

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---+- 3 Relays-MSRS-Flat � 3 Relays-MARS-Flat - • - 3 Relays-MSRS-Selective - � - 3 Relays-MARS-Selective

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'---_-'---_--'-_---'__-'---_--'-_---'_---' 10-2 L-_--'---_---'-_---' 20 o 10 12 14 16 18 SNR(dBJ

Fig. 5. BER performance comparison of MSRS and MARS in three relays system with Cl = 1, C2 = 2, C3 = 4 over selective and flat Rayleigh fading channels.

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