DocumentCode :
443866
Title :
Application of a genetic algorithm to Hopfield network multi-user detection
Author :
Ying, Zhang ; HongLi, Liu ; Fei, Kuang ; Jia, Chen
Author_Institution :
Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
Volume :
1
fYear :
2005
fDate :
23-26 Sept. 2005
Firstpage :
644
Lastpage :
647
Abstract :
In this study, a hybrid approach that employs Hopfield network and a genetic algorithm for multi-user detection problem in code division multiple access system is proposed. The hybrid detection makes use of the global convergence advantage of the genetic algorithm to deal with the output of the Hopfield network detection. So the novel detection will not converge on the minimum of local energy function as the Hopfield network detection. And the computer simulation results show that this detection has good performance both in multiple-access interference resistance and near-far effect resistance.
Keywords :
Hopfield neural nets; code division multiple access; genetic algorithms; interference; multiuser detection; telecommunication computing; Hopfield network multiuser detection; code division multiple access system; genetic algorithm; local energy function; multiple-access interference resistance; near-far effect resistance; Detectors; Educational institutions; Genetic algorithms; Genetic engineering; Hopfield neural networks; Matched filters; Multi-layer neural network; Multiaccess communication; Multiple access interference; Multiuser detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2005. Proceedings. 2005 International Conference on
Print_ISBN :
0-7803-9335-X
Type :
conf
DOI :
10.1109/WCNM.2005.1544126
Filename :
1544126
Link To Document :
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