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Multi‐relay selection schemes based on evolutionary algorithm in cooperative relay networks
Author(s) -
Cao Jinlong,
Zhang Tiankui,
Zeng Zhimin,
Chen Yue,
Chai Kok Keong
Publication year - 2014
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.2710
Subject(s) - relay , maximization , computer science , mathematical optimization , selection (genetic algorithm) , sorting , optimization problem , multi objective optimization , evolutionary algorithm , power (physics) , algorithm , mathematics , artificial intelligence , physics , quantum mechanics
SUMMARY 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.