• DocumentCode
    538933
  • Title

    Multiuser Detection Based on the DNA Clonal Selection Algorithm

  • Author

    Gao, Hongyuan ; Cao, Jinlong ; Yu, Xuemei

  • Author_Institution
    Coll. of Inf. & Commun. Eng., Harbin Eng. Univ., Harbin, China
  • Volume
    2
  • fYear
    2010
  • fDate
    16-17 Dec. 2010
  • Firstpage
    349
  • Lastpage
    352
  • Abstract
    In this paper, a novel multi-user detection based on a DNA clonal selection algorithm (DNACSA) is proposed for code-division multiple-access communications system. To design an efficient DNACSA based detector, the stochastic Hop field neural network is embedded into the DNACSA as an “immune operator” to improve further the affinity of the DNA antibodies at each generation. Such a hybridization of the DNACSA with the stochastic Hop field neural network reduces its computational complexity by providing faster convergence. In addition, the embedded Hop field neural network improves the performance of the DNACSA. Simulation results are provided to show that the proposed DNACSA detector has significant performance improvements over the conventional detectors and some detectors based on the previous intelligence algorithms in bit-error-rate and multiple access interference resistance.
  • Keywords
    DNA; Hopfield neural nets; biocomputing; code division multiple access; computational complexity; convergence; genetic algorithms; multiuser detection; DNA antibody; DNA clonal selection algorithm; DNACSA based detector; bit error rate; code division multiple access communication system; computational complexity; immune operator; intelligence algorithm; multiple access interference resistance; multiuser detection; stochastic Hopfield neural network; DNA; Detectors; Gallium; Hopfield neural networks; Multiaccess communication; Multiuser detection; Optimization; DNA computation; clonal selection algorithm; code division multiple access (CDMA); multiuser detection; neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9247-3
  • Type

    conf

  • DOI
    10.1109/GCIS.2010.218
  • Filename
    5709283