Fairness-aware resource partition and routing in relay-enhanced orthogonal-frequency-division-multiple-accessing cellular networks

Abstract

Unlike conventional cellular networks where the evolved Node B (eNB) performs centralised scheduling, future relayenhanced cellular (REC) networks allow relay nodes (RNs) to schedule users independently. This decentralised nature of the REC networks brings about challenges to maintain fairness. In this study, we formulate the generalised proportional fair (GPF) resource allocation problem, where resource partition and routing are included as part of the overall radio resource management aiming to provide fairness across all users served by the eNB and its subordinate RNs. Although the traditional proportional fair scheduling algorithm is executed independently at the eNB and each RN to maintain local fairness, we propose efficient resource partition and routing algorithms to maintain global fairness by optimising the GPF objective for the whole relay-enhanced cell. Through system level simulations, the proposed algorithms are evaluated and compared with both non-relaying and relaying systems with benchmark resource partition and routing algorithms. The simulation results show that the proposed algorithms outperform the existing algorithms in providing a better trade-off between system throughput and fairness performance.

Radio resource management for user-relay assisted OFDMA-based wireless networks

“…The total transmission power is equally shared among all subchannels. We assume that all required channel gains among BS and all UEs, and among UEs and user-relays are available perfectly at the BS where RA algorithms are performed as in user-relay assisted OFDMA systems [32][33][34][35][36][37][38] as well as fixed-relay assisted OFDMA systems [19][20][21][22][23][24][25][26][27][28][29]. The communication links between BS and userrelays and user-relays and UEs use the same subchannel at different time slots as in [32,37,38].…”

“…The problem formulation may differ significantly in optimization objectives (rate maximization, power minimization), optimization constraints (fairness, load balancing), relaying protocols (amplify and forward (AF), decode and forward (DF)), relaying modes (full-duplex, half-duplex), relay types (fixed, mobile), antenna numbers of the source, destination and relay (single antenna/multiple antennas) and system architectures (downlink/uplink, single-cell/multi-cell). The RRM problem has been examined in numerous research works for OFDMA-based fixed relay networks [19][20][21][22][23][24][25][26][27][28][29]. The opportunities and challenges of the OFDMA-based fixed relay networks have been discussed in detail in [19,20].…”

“…In [22], a low complexity heuristic solution has been presented for the same RRM problem. The fairness issue has been considered in [23][24][25] contrary to given studies earlier and heuristic RRM algorithms have been presented. In [26,27], the joint relay selection and RA problem have been investigated for the uplink single-cell OFDMA-based system.…”

Joint Optimization Methods for Nonconvex Resource Allocation Problems of Decode-and-Forward Relay-Based OFDM Networks

“…Many novel resource allocation methods have been studied for these systems recently that can be divided into two strategies based on the optimization objectives. One is focus on maximizing the total end-to-end transmission rate under the constraint of a total resource (power and bandwidth) [3][4][5][6], while the other one lays emphasis on finding the minimum energy consumption with a given data rate requirements [7][8][9][10]. The two strategies follows the famous Rate Adaptive (RA) and Margin Adaptive (MA) criterion in the field of adaptive resource allocation, respectively.…”

“…Such kind of works could not achieve a perfect performance because AF relay would amplify the noise while transmit useful signals. In addition, the authors of [3,5,8,[14][15] proposed adaptive resource assignment schemes for OFDM-relay networks in which relays are regarded as cooperation nodes without specific strategy which could not be applied in the real communication system.…”