An efficient resource allocation algorithm for OFDMA cooperative relay networks with fairness and QoS guaranteed

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1 Univerity of Wollongong Reearch Online Faculty of Informatic - Paper (Archive) Faculty of Engineering and Information Science 200 An efficient reource allocation algorithm for OFDMA cooperative relay network with fairne and QoS guaranteed Aem A. Salah Univeriti Putra Malayia Borhanunddin Mohd. Ali Univeriti Putra Malayia Ahmad Saqer Univeriti Putra Malayia Nidhal Odeh Univerity of Wollongong Publication Detail Salah, A. A., Ali, B. Mohd., Saqer, A. & Odeh, N. (200). An efficient reource allocation algorithm for OFDMA cooperative relay network with fairne and QoS guaranteed. Proceeding: Second International Conference on Network Application, Protocol and Service (NETAPPS 200) (pp ). IEEE. Reearch Online i the open acce intitutional repoitory for the Univerity of Wollongong. For further information contact the UOW Library: reearch-pub@uow.edu.au

2 An efficient reource allocation algorithm for OFDMA cooperative relay network with fairne and QoS guaranteed Abtract Thi paper propoe a new reource allocation algorithm for uplink OFDMA-baed cooperative relay network auming multiple ource node, multiple relay node and a ingle detination. The aim i to maximize the total um of the ource data rate while guaranteeing fairne among them with different QoS requirement. Auming perfect channel tate information (CSI) at the reource allocation controller. The optimization problem i formulated uch that each ource i aigned a weight factor baed on it QoS requirement, then the one with high weight are given more priority to elect their reource (relay tation and ubcarrier) firt. Once the required QoS i achieved for all ource, the weight factor for all ource will be unity. The remaining reource are allocated to the ource with maximum intantaneou rate. The reult how that the propoed algorithm outperform the greedy and tatic algorithm in term of outage probability and fairne. Dicipline Phyical Science and Mathematic Publication Detail Salah, A. A., Ali, B. Mohd., Saqer, A. & Odeh, N. (200). An efficient reource allocation algorithm for OFDMA cooperative relay network with fairne and QoS guaranteed. Proceeding: Second International Conference on Network Application, Protocol and Service (NETAPPS 200) (pp ). IEEE. Thi conference paper i available at Reearch Online:

3 200 Second International Conference on Network Application, Protocol and Service An Efficient Reource Allocation Algorithm for OFDMA Cooperative Relay Network with Fairne and QoS Guaranteed Aem A. Salah, Borhanuddin Mohd. Ali, Ahmad Saqer and Nidhal Odeh Department of Computer and Communication Sytem Engineering Faculty of Engineering, Univeriti Putra Malayia UPM Serdang, Malayia ICT Reearch Intitute, Faculty of Informatic Univerity of Wollongong, Wollongong NSW 2522 Autralia Abtract Thi paper propoe a new reource allocation algorithm for uplink OFDMA-baed cooperative relay network auming multiple ource node, multiple relay node and a ingle detination. The aim i to maximize the total um of the ource data rate while guaranteeing fairne among them with different QoS requirement. Auming perfect channel tate information (CSI) at the reource allocation controller. The optimization problem i formulated uch that each ource i aigned a weight factor baed on it QoS requirement, then the one with high weight are given more priority to elect their reource (relay tation and ubcarrier) firt. Once the required QoS i achieved for all ource, the weight factor for all ource will be unity. The remaining reource are allocated to the ource with maximum intantaneou rate. The reult how that the propoed algorithm outperform the greedy and tatic algorithm in term of outage probability and fairne. Index Term Cooperative Relay, OFDMA, Reource Allocation, QoS Requirement, Fairne. I. INTRODUCTION AND RELATED WORK Orthogonal Frequency Diviion Multiple Acce (OFDMA) i conidered a one of the mot effective olution to provide a high performance tranmiion in emerging cellular network in the 4 th Generation (4G) network. OFDMA eliminate the frequency electivity effect by tranmitting the wideband ignal on multiple orthogonal narrow-band ub-channel called ubcarrier. Thi allow different node to ue pectrally overlapped ub-channel imultaneouly without interfering with each other, hence the pectral utilization i increaed ignificantly. Recently cooperative relaying ha emerged a a promiing technique for future generation of cellular network by way of virtual patial diverity. In cooperative tranmiion, the ource tranmit information to a detination with the aitance of one or more relay node called Relay Station (RS) which i uppoed to improve the overall network performance, e.g., coverage extenion, throughput increae, interference mitigation and power aving []. The mot popular cooperative relaying method are Amplifyand-Forward (AF) (non-regenerative relay) and Decode-and- Forward(DF) (regenerative relay) method. In AF relaying, the relay amplifie and retranmit a noiy verion of the received ignal without any attempt to decode it, while in DF relaying, the relay node fully decode, re-encode, and retranmit the noiy verion of the received ignal by the ource node [2], [3]. The OFDMA cooperative relay network are expected to provide high-peed broadband ervice that provide QoS guarantee for data, voice and video traffic. Reource allocation for OFDMA network can be claified into two categorie according to the objective function. The firt objective i to minimize the tranmit power given a data rate contraint; thi i called power minimization alo known a margin adaptive [4]. In the econd category the data rate i maximized under power contrain; thi i called rate maximization alo known a rate adaptive [5], [6]. Thi paper focue on the latter. The reource allocation and optimization in OFDMA ytem have been extenively invetigated in the literature. However, the fact that thoe different ource (uer) may tranmit different type of data (voice, text, video, etc) with different rate requirement ha been ignored in mot of the propoed algorithm [4], [7], [8]. Thu, in thi paper, we propoe a reource allocation algorithm which upport multiuer each with different rate requirement. The author in [4] propoed a heuritic ubcarrier and power allocation algorithm. The algorithm i divided into two ubproblem; firtly, the ubcarrier are allocated to uer and then the power i aigned acro thee ubcarrier. Significant improvement on ytem performance were achieved uing thi algorithm. However, no fairne or QoS requirement are incorporated in the algorithm. The fairne iue wa taken into account in [7]. The author in [7] propoed a centralized cheduling cheme called centralized cheduling with void filling (CS-VF). In CS-VF, four repreentative inglehop cheduling algorithm: round-robin, max C/I, max-min /0 $ IEEE DOI 0.09/NETAPPS

4 fairne, and proportional fairne, are extended to multihop cenario. The propoed algorithm trie to achieve fairne by making a balance between the achieved rate for the ource, independent of their rate requirement. The author in [8] followed a imilar approach a in [4] however, unlike [4]; in [8] the fairne iue wa conidered. To maintain the fairne among uer, the propoed algorithm allocate equal number of ubcarrier. However, thi i only valid when all uer are tranmitting the ame type of data. Thu, uer with high rate requirement will be allocated the ame number of ubcarrier a the one with low rate requirement. In thi paper, we propoe a imple reource allocation algorithm for OFDMA cooperative relay network with QoS minimum rate requirement guarantee. The main idea i to allocate the ubcarrier to the ource whoe traffic contraint i going to be violated while at the ame time ha the bet channel condition (intantaneou rate). In our propoed algorithm, a ervice weight factor parameter i defined, by which each ource get a weight baed on it QoS rate requirement; the ource with the larget QoS minimum rate requirement get the highet weight and vice vera. Then the weighted intantaneou rate i calculated for each ource to allocate the ubcarrier for the ource-relay pair that ha the maximum weighted intantaneou rate. The ret of thi paper i organized a follow. The ytem model i provided and the optimization problem i formulated in ection II, followed by Section III which preent the propoed ubcarrier allocation. The numerical reult are dicued in ection IV. Finally, ection V conclude the paper. II. SYSTEM MODEL AND PROBLEM FORMULATION A. Sytem Model A hown in Figure, the adopted ytem model aume an uplink multiuer OFDMA cooperative relay network, with S ource node, R relay node and ingle detination (D) node /(BS) in a ingle cell cenario. The available ource within the cell hare a number of N ubcarrier, thee ubcarrier are available at the BS to be allocated to ource according to their individual need baed on the intantaneou full channel tate information (CSI). Let S = {,...,,..., S}, R = {,..., r,..., R} and N = {,..., n,..., N} denote the et of the ource, relay, and ubcarrier, repectively. The QoS of the th ource i denoted a Q which i decribed the minimum rate requirement of that ource in bit/ec/hz. Thu, we can denote a et of minimum rate requirement for all ource a, Q = {Q,..., Q,..., Q S }. Aume that the detination bae tation receive the ame ignal from the participating relay tation a well a directly from the ource. Furthermore, aume that tranmiion lot (T ) i divided to two half, i.e. the ource tranmit while the relay tation and bae tation receive in the firt half, and the relay tation tranmit the received ignal to the bae tation uing either AF or DF during the econd half [5], [6], [8]. Fig.. Sytem model for an uplink multiuer OFDMA relay network, the different hape of S denote different ervice (different QoS requirement) Baed on the QoS requirement of the ervice/ource node and CSI full knowledge, the central reource allocation unit at BS perform the reource allocation and optimization, uch that the total throughput i maximized ubject to QoS and maximum power contraint, Then the BS inform the ource and relay about their aigned ubcarrier. Thi proce i illutrated in Figure 2. Furthermore, It i aumed that all wirele channel between any two node experience frequencyelective low fading with a coherence bandwidth greater than the tranmitted narrow-band ignal bandwidth. Over a certain ubcarrier n, the channel coefficient between the ource and the detination D i denoted a H (n),d, imilarly, the channel between the th ource and the r th relay denoted by H,r (n), and finally, H (n) r,d denote the channel between the rth relay and the detination D. R S r R S Fig. 2. SC n N Subcarrier Allocation Weight Factor CSI QoS Requirement Channel Etimator Feedback ignal Weight baed reource allocation block diagram The intantaneou rate of the ource over the n th and with the aitance of the r th relay tation, can be written in equation and 2 uing the AF and DF relay cheme repectively [5] R,r (n) = 2 log H (n),d N 0 H,r (n) 2 (n) H r,d 2 r H,r (n) 2 + H (n) r,d 2 r + N 0 N 0 Rx () 89

5 R,r (n) = 2 min log H (n),r 2 2 +, N 0 H (n),d 2 H (n) r,d 2 r log N 0 N 0 Where, x denote the power allocated to the node x over ubcarrier n, N 0 denote the ingle-ided power pectral denity of AWGN, and it i aumed to be equal for all ubcarrier in a wirele network (i.e. N 0 =). To avoid the interference, each ubcarrier i occupied by only one ourcerelay pair in each tranmiion [8]. Therefore we defined,r to denote the ubcarrier aignment indicator variable, where { if ubcarrier n allocated to ource and relay r;,r = 0 otherwie (3) The total um rate achieved by the ource over all allocated ubcarrier to that ource i given by R = r= n= (2),r (4) Thu, the total network achievable rate i the um of the total achievable rate by each ource, thu, we can write R = R (5) = B. Problem Formulation Thi ection formulate the optimization problem. A tated earlier, the objective function i to maximize the achievable data rate ubject to minimum rate requirement by each ource and maximum power contraint. Furthermore, the fairne among ource i taken into account. In fact, thi fairne contraint will caue degradation on the total achievable rate. However, the optimum rate cannot guarantee the fairne and hence, we acrifice a mall amount of data rate in order to enure that each ource i able to meet it rate requirement with a imilar probability a other. On the other hand, the fairne among relay i achieved by limiting the maximum tranmiion power for each relay to P r. Mathematically, the objective i to maximize equation (5). By ubtituting (4) in (5) and taking into account the contraint, the formulated optimization problem can be written a ubject to: R = max = r= n=,r {0, },, r, n,r (6) (7a) = (r=) n= n=,r =, n (7b) P, (7c) r P r, r (7d) 0, n, (7e) r= n= r 0, n, r (7f),r Q, (7g) Where, contraint (7a) and (7b) indicate that ubcarrier are excluively allocated to one ource-relay pair to avoid interference between ource. Contraint (7c)-(7f) are the maximum and the minimum tranmiion power by each ource and relay repectively and contraint (7g) wa impoed to enure fairne among different ource. It can be een that the optimization problem in (6) contain both continuou repectively). Thu, thi made the problem combinatorial optimization problem which i computationally complex to obtain a global optimal olution. To implify the matter, thi paper focue on the ubcarrier allocation rather than the power allocation, hence equal power allocation for each ource and relay i adopted. Thi i a valid aumption becaue it wa hown that equal power allocation achieve imilar performance to the waterfilling power allocation which i conidered the optimal power allocation [9] []. Thu, the optimization problem in (6) become and integer variable (i.e., R n,r and,r R = max = r= n=,r {0, },, r, n = (r=) r= n=,r =, n,r Q,,r (8) (9a) (9b) (9c) III. PROPOSED SUBCARRIER ALLOCATION Baed on the optimization problem in (8) and taking into conideration the contrain (9a)-(9c), we preent the propoed ubcarrier allocation algorithm. Thi illutrated in Algorithm. The algorithm conit of two tep:- Initialization and Subcarrier allocation. In the firt tep the et of parameter are initialized. The main proce i performed during the ubcarrier allocation tep, in which the algorithm optimize the allocation of available ubcarrier baed on the given parameter on the initialization tep. 90

6 At the beginning, each ource i given a weight which i correpond to the ource QoS requirement. The weight vector w i,i =,...,,..., S repreent the difference between each ource rate requirement and it achieved rate o far. Thu, the ource with high rate requirement will have a higher weight and thu are given higher priority to elect their bet ubcarrier firt. However, other ource with lower priority will be allowed to elect certain ubcarrier firt if that particular ubcarrier ha a high channel gain on that low rate requirement ource. Thu, the rate reduction due to fairne contraint i minimized. Thi i performed by multiplying the weight value of each ource (w ) with the intantaneou rate R,r (n) (i.e. Rw = w R,r (n) ) ahowninalgorithm. Thu, for a certain ubcarrier the winner will be the ource-relay pair with the higher value of Rw. Thi will prevent the high rate requirement ource from utilizing the bet ubcarrier with repect to other lower rate requirement ource when thoe ubcarrier have a low channel gain on the high rate requirement ource. Thu, the lower rate requirement ource are alo given a chance to utilize the bet available ubcarrier on them to maximize the total network rate, and vice vera. Once the minimum rate requirement for all ource are achieved, then all ource will have a unity Weight; a a reult, the ubcarrier are allocated to the ource-relay pair that have the larget intantaneou rate, which maximize the total um rate. So, a ingle ource-relay pair will be elected to utilize a certain ubcarrier by which the Rw value i maximized. Thi proce will continue a long a there are unallocated ubcarrier, and once all the ubcarrier are allocated the algorithm will end and give the allocation vector. Algorithm Propoed Subcarrier Allocation Algorithm Step : Initialization Set S = {, 2,,S}, R = {, 2,,R}, N = {, 2,,N}, Q = {Q,Q 2,,Q S },R =0, S,,r =0,, r, n; Step 2: Subcarrier Allocation for n =: N do w = Q R, {S} Rw = w R (n) (, r )=arg,r,r update R end for,r, {S}, r {R} max Rw, {S}, r {R} =, N = N {n} IV. NUMERICAL RESULTS The performance of propoed ubcarrier allocation algorithm wa evaluated in term of the achieved total um rate, fairne, and outage probability. The algorithm wa compared with the greedy and tatic ubcarrier allocation algorithm uing equal power allocation. Greedy algorithm i conidered Total Sum Rate (bp/hz) Propoed, DF Greedy, DF Static, DF Propoed, AF Greedy, AF Static, AF SNR (db) Fig. 3. Total um rate for the propoed ubcarrier allocation algorithm for both AF and DF. N=28, R=2 and S=3 a the algorithm can give maximum achievable throughput in [8]. in addition to the fact that it i the olution to the problem in [2]. In greedy algorithm the ubcarrier i allocated to the ourcerelay pair which ha the larget intantaneou rate. The tatic ubcarrier allocation algorithm i a modified of the tatic FDMA in [3] and [4], in tatic ubcarrier allocation algorithm, an equal number of ubcarrier (N/S) are allocated to each ource-relay pair in the ytem. Figure 3 how the um rate of the propoed algorithm againt the greedy and tatic algorithm for AF and DF. The imulation wa averaged over 000 iteration, in each iteration different ource are aigned with a different data rate requirement. Thee data rate requirement were normalized to have a random value between 0 and. The parameter (N, R and S) have been choen according to [8], to make a fair comparion with the algorithm propoed in [8]. The propoed algorithm outperform the tatic algorithm under any SNR (about 9.84 bp/hz and 2.6 bp/hz higher than the tatic for AF and DF repectively at SNR=25 db). On the other hand, the greedy algorithm achieve a lightly higher total um rate compared to our propoed algorithm (about 0.7 bp/hz lower than greedy algorithm for both AF and DF at SNR=25 db). However, the greedy algorithm work in a elfih manner and hence fairne i not guaranteed, which i why it i conidered a an optimum algorithm to maximize data rate regardle of fairne [8]. Thu, it i worth to acrifice a mall amount of data rate in order to achieve fairne among different ource. Figure 4 how the outage probability of the propoed algorithm compared to greedy and tatic algorithm. In thi figure an outage event will occur if at leat one ource doe not achieve it minimum rate requirement. The outage probability graph obtained from the average of 000 iteration. It can be een that the propoed algorithm ha le outage event compared to the greedy algorithm; thi jutifie the reult 9

7 Outage probability Fig. 4. S=0 Rate (bp/hz) Propoed Greedy Static SNR (db) Outage probability for the propoed algorithm, N=28, R=4 and Rmin propoed 0.2 Greedy Static Uer Fig. 5. Source achievable rate compared with the ource minimum rate requirement. N=28, R=4, S=0 and SNR=0dB of Figure 3, i.e, the trade-off between the achievable rate and the outage probability. With repect to the tatic algorithm, the figure how that the propoed algorithm achieve a ignificant performance improvement over the tatic algorithm. Thi i alo intuitive becaue the tatic algorithm i characterized by it inflexibility and thu more outage event will occur. Fairne among uer i conidered to be achieved if all ource are able to achieve their minimum data rate requirement. Auming different ource with different rate requirement, Figure 5 depict the achieved rate uing the propoed, greedy and tatic algorithm compared to the minimum rate requirement for each ource. A hown in the figure, uing the propoed algorithm, all ource were able to achieve their minimum data rate requirement. In contrat, only few ource were able to achieve their minimum rate requirement uing the greedy algorithm and only one ource achieved hi requirement uing tatic algorithm. V. CONCLUSION In thi paper we propoed an efficient and imple reource allocation algorithm for the OFDMA cooperative relay network. The achievable data rate were maximized while at the ame time maintaining fairne among uer. The propoed algorithm wa compared with other algorithm (greedy and tatic) and the reult how that the propoed algorithm outperform the other two in term of outage probability and fairne. The achieved data rate wa almot imilar with the greedy algorithm, but much higher than tatic algorithm. REFERENCES [] Danhua Zhang, Youzheng Wang, and Jianhua Lu. On QoS-Guaranteed downlink cooperative OFDMA ytem with Amplify-and-Forward relay: Optimal chedule and reource allocation. In Wirele Communication and Networking Conference, WCNC IEEE, page 5, [2] Yanwu Ding and M. Uyal. Amplify-and-forward cooperative OFDM with multiple-relay: performance analyi and relay election method. Wirele Communication, IEEE Tranaction on, 8(0): , [3] M. Torabi, W. Ajib, and D. Haccoun. Performance analyi of Amplifyand-Forward cooperative network with relay election over rayleigh fading channel. In Vehicular Technology Conference, VTC Spring IEEE 69th, page 5, [4] Lei Huang, Mengtian Rong, Lan Wang, Yiheng Xue, and E. Schulz. Reource allocation for OFDMA baed relay enhanced cellular network. In Vehicular Technology Conference, VTC2007-Spring. IEEE 65th, page , [5] Hyundoo Jeong, Jae Hong Lee, and Hanbyul Seo. Reource allocation for uplink multiuer OFDM relay network with fairne contraint. In Vehicular Technology Conference, VTC Spring IEEE 69th, page 5, [6] M.K. Awad and Xuemin Shen. OFDMA baed Two-Hop cooperative relay network reource allocation. In Communication, ICC 08. IEEE International Conference on, page , [7] Liping Wang, Yuheng Ji, and Fuqiang Liu. A novel centralized reource cheduling cheme in OFDMA-Baed Two-Hop Relay-Enhanced cellular ytem. In Networking and Communication, WIMOB 08. IEEE International Conference on Wirele and Mobile Computing,, page 3 8, [8] Hongxing Li, Hanwen Luo, Xinbing Wang, and Chiheng Li. Throughput maximization for OFDMA cooperative relaying network with fair ubchannel allocation. In Wirele Communication and Networking Conference, WCNC IEEE, page 6, [9] Jiho Jang and Kwang Bok Lee. Tranmit power adaptation for multiuer OFDM ytem. Selected Area in Communication, IEEE Journal on, 2(2):7 78, [0] Keunyoung Kim, Youngnam Han, and Seong-Lyun Kim. Joint ubcarrier and power allocation in uplink OFDMA ytem. Communication Letter, IEEE, 9(6): , [] W. Rhee and J.M. Cioffi. Increae in capacity of multiuer OFDM ytem uing dynamic ubchannel allocation. In Vehicular Technology Conference Proceeding, VTC 2000-Spring Tokyo IEEE 5t, volume 2, page vol.2, [2] Guoqing Li and Hui Liu. Reource allocation for OFDMA relay network with fairne contraint. Selected Area in Communication, IEEE Journal on, 24(): , [3] Jian Xu, Wonkyu Paik, Jongkyung Kim, and Jong-Soo Seo. Dynamic ubcarrier and power allocation with proportional rate contraint for multi-uer pace-time block-coded ofdm ytem. In Vehicular Technology Conference, VTC2007-Spring. IEEE 65th, page , April [4] Bin Da, C.C. Ko, and Yanfen Liang. An enhanced capacity and fairne cheme for mimo-ofdma downlink reource allocation. In Communication and Information Technologie, ISCIT 07. International Sympoium on, page , Oct