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Investigation on the evolutionary algorithms with their applications in MIMO detecting systems
Author(s) -
Hei YongQiang,
Li Xiao-Hui,
Li WenTao
Publication year - 2013
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.2317
Subject(s) - particle swarm optimization , computer science , mimo , genetic algorithm , algorithm , evolutionary algorithm , population , multi swarm optimization , mathematical optimization , artificial intelligence , machine learning , mathematics , telecommunications , channel (broadcasting) , demography , sociology
SUMMARY In this paper, with the purpose of integrating the advantages of both the genetic algorithm and the particle swarm optimization, a new genetic particle swarm optimization (GPSO) algorithm is proposed. Furthermore, these three evolutionary algorithms are successfully applied to address the MIMO detection problem. Simulation results reveal that the GPSO‐based detection algorithm takes much less population size and iteration number when compared with the particle swarm optimization‐based detection method and the genetic algorithm‐based detection method. Besides, when compared with the optimal maximum likelihood detection method, the GPSO‐based detection algorithm can strike a much better balance between the BER performance and the computational complexity. Copyright © 2012 John Wiley & Sons, Ltd.