• 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