Multi‐relay selection schemes based on evolutionary algorithm in cooperative relay networks

In cooperative relay networks, the selected relay nodes have great impact on the system performance. In this paper, a multi-relay selection schemes that consider both single objective and multi-objective are proposed based on evolutionary algorithms. First, the single-objective optimization problems of the best cooperative relay nodes selection for signal-to-noise ratio SNR maximization or power efficiency optimization are solved based on the quantum particle swarm optimization QPSO. Then the multi-objective optimization problems of the best cooperative relay nodes selection for SNR maximization and power consumption minimization two contradictive objectives or SNR maximization and power efficiency optimization also two contradictive objectives are solved based on a non-dominated sorting QPSO, which can obtain the Pareto front solutions of the problems considering two contradictive objectives simultaneously. The relay systems can select one solution from the Pareto front solutions according to the trade-off of SNR and power consumption or the trade-off of SNR and power efficiency to take part in the cooperative transmission. Simulation results show that the QPSO-based multi-relay selection schemes have the ability to search global optimal solution compared with other multi-relay selection schemes in literature. Simulation results also show that the non-dominated sorting QPSO-based multi-relay selection schemes obtain the same Pareto solutions as exhaustive search, but the proposed schemes have a very low complexity. Copyright © 2013 John Wiley & Sons, Ltd.

[1]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[2]  Russell C. Eberhart,et al.  A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[3]  Yifan Li,et al.  A dynamic relay selection scheme for mobile users in wireless relay networks , 2011, 2011 Proceedings IEEE INFOCOM.

[4]  Anchare V. Babu,et al.  Maximizing the data transmission rate of a cooperative relay system in an underwater acoustic channel , 2012, Int. J. Commun. Syst..

[5]  Aria Nosratinia,et al.  Cooperative communication in wireless networks , 2004, IEEE Communications Magazine.

[6]  Yindi Jing,et al.  Network Beamforming Using Relays With Perfect Channel Information , 2007, IEEE Transactions on Information Theory.

[7]  Yindi Jing,et al.  Single and multiple relay selection schemes and their achievable diversity orders , 2009, IEEE Transactions on Wireless Communications.

[8]  Zhen Peng,et al.  Cognitive radio spectrum allocation using evolutionary algorithms , 2009, IEEE Transactions on Wireless Communications.

[9]  Qimei Cui,et al.  Energy-Efficient Relay Selection and Power Allocation for Two-Way Relay Channel with Analog Network Coding , 2012, IEEE Communications Letters.

[10]  Dongmei Jiang,et al.  Joint precoding and power allocation for multiuser transmission in MIMO relay networks , 2012, Int. J. Commun. Syst..

[11]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[12]  Tiankui Zhang,et al.  Multi-relay selection scheme based on quantum particle swarm optimization in relay networks , 2012, The 15th International Symposium on Wireless Personal Multimedia Communications.

[13]  Norman C. Beaulieu,et al.  Exact Analysis of Dual-Hop AF Maximum End-to-End SNR Relay Selection , 2012, IEEE Transactions on Communications.

[14]  Farrokh Etezadi,et al.  Decentralized Relay Selection Schemes in Uniformly Distributed Wireless Sensor Networks , 2012, IEEE Transactions on Wireless Communications.

[15]  Abdelfatteh Haidine.  Design of reliable fiber-based distribution networks modeled by multi-objective combinatorial optimization , 2013, Int. J. Commun. Syst..

[16]  Ali Peiravi,et al.  An optimal energy‐efficient clustering method in wireless sensor networks using multi‐objective genetic algorithm , 2013, Int. J. Commun. Syst..

[17]  Kalyanmoy Deb,et al.  Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms , 1994, Evolutionary Computation.

[18]  Wenbo Wang,et al.  Performance analysis of the unicasting mode in multi-relay systems , 2011, Int. J. Commun. Syst..

[19]  Kalyanmoy Deb,et al.  A Hybrid Framework for Evolutionary Multi-Objective Optimization , 2013, IEEE Transactions on Evolutionary Computation.

[20]  Hong Ji,et al.  An Energy-Efficient Distributed Relay Selection and Power Allocation Optimization Scheme over Wireless Cooperative Networks , 2011, 2011 IEEE International Conference on Communications (ICC).

[21]  Marco Laumanns,et al.  SPEA2: Improving the strength pareto evolutionary algorithm , 2001 .

[22]  Xiaohua Li,et al.  Optimal multiple-relay selection in dual-hop amplify-and-forward cooperative networks , 2012 .