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

被引:17
作者
Cao, Jinlong [1 ]
Zhang, Tiankui [1 ]
Zeng, Zhimin [1 ]
Chen, Yue [2 ]
Chai, Kok Keong [2 ]
机构
[1] Beijing Univ Posts & Telecom, Beijing Key Lab Network Syst Architecture & Conve, Beijing, Peoples R China
[2] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London, England
基金
英国工程与自然科学研究理事会;
关键词
cooperative relay; multi-relay selection; evolutionary algorithm; power efficiency; POWER ALLOCATION; TRANSMISSION; CHANNEL;
D O I
10.1002/dac.2710
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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 (c) 2013 John Wiley & Sons, Ltd.
引用
收藏
页码:571 / 591
页数:21
相关论文
共 23 条
[1]  
[Anonymous], 2009, TR 36.814 V9.0.0
[2]   Maximizing the data transmission rate of a cooperative relay system in an underwater acoustic channel [J].
Babu, A. V. ;
Joshy, Susan .
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2012, 25 (02) :231-253
[3]   REMARKS ON LIPSCHITZ p-SUMMING OPERATORS [J].
Chen, Dongyang ;
Zheng, Bentuo .
PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY, 2011, 139 (08) :2891-2898
[4]  
Deb, 1994, EVOLUTIONARY COMPUTA, V2, P221, DOI DOI 10.1162/EVCO.1994.2.3.221
[5]   A fast and elitist multiobjective genetic algorithm: NSGA-II [J].
Deb, K ;
Pratap, A ;
Agarwal, S ;
Meyarivan, T .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197
[6]   Decentralized Relay Selection Schemes in Uniformly Distributed Wireless Sensor Networks [J].
Etezadi, Farrokh ;
Zarifi, Keyvan ;
Ghrayeb, Ali ;
Affes, Sofiene .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2012, 11 (03) :938-951
[7]  
Haidine A., 2012, INT J COMMUNICATION, DOI [10.1002/dac.1391, DOI 10.1002/DAC. 1391]
[8]   Joint precoding and power allocation for multiuser transmission in MIMO relay networks [J].
Jiang, Dongmei ;
Zhang, Haixia ;
Yuan, Dongfeng .
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2012, 25 (02) :205-220
[9]   Network Beamforming Using Relays With Perfect Channel Information [J].
Jing, Yindi ;
Jafarkhani, Hamid .
IEEE TRANSACTIONS ON INFORMATION THEORY, 2009, 55 (06) :2499-2517
[10]   Single and Multiple Relay Selection Schemes and their Achievable Diversity Orders [J].
Jing, Yindi ;
Jafarkhani, Hamid .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2009, 8 (03) :1414-1423