• DocumentCode
    711950
  • Title

    Multi-relay Selection in Decode-and-Forward Cooperative Network Based on Genetic Algorithm

  • Author

    Xiaolong Dai ; Jing Zhang ; Qian Zhang

  • Author_Institution
    Coll. of Inf. Machine & Electr. Eng., Shanghai Normal Univ., Shanghai, China
  • fYear
    2015
  • fDate
    24-26 April 2015
  • Firstpage
    834
  • Lastpage
    837
  • Abstract
    A novel multi-relay selection algorithm based on genetic algorithm (GA) in dual-hop decode- and-forward cooperative network is presented. The quality of service is expressed by the condition that the SNR of destination should be larger than 22R -- 1 according to Shannon information capacity, in which R is its data-rate requirement. Moreover, residual energy status parameter of the network using the total energy of each node along with [0, 1] indicator are modelled in order to prolong the network lifetime. The optimization problem is to minimize the residual energy under the SNR condition. It is a NP-complete one, and a general GA is exploited to search out the solution. Simulation results show that the proposed algorithm can preserve the network lifetime much longer than opportunistic relay.
  • Keywords
    computational complexity; cooperative communication; decode and forward communication; genetic algorithms; information theory; quality of service; relay networks (telecommunication); GA; NP-complete problem; SNR; Shannon information capacity; data-rate requirement; dual-hop decode-and-forward cooperative network; genetic algorithm; multirelay selection; network lifetime; quality of service; residual energy status parameter; Biological cells; Cooperative systems; Genetic algorithms; Quality of service; Relays; Sociology; Statistics; Cooperative Network; Genetic Algorithm; Multi-relay Selection; Network Lifetime;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Control Engineering (ICISCE), 2015 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4673-6849-0
  • Type

    conf

  • DOI
    10.1109/ICISCE.2015.190
  • Filename
    7120730