• DocumentCode
    2934606
  • Title

    Adaptive Resource Allocation in Multiuser OFDM System Based on Genetic Algorithm

  • Author

    Liu, Bo ; Jiang, Mingyan ; Yuan, Dongfeng

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan
  • Volume
    1
  • fYear
    2009
  • fDate
    6-8 Jan. 2009
  • Firstpage
    270
  • Lastpage
    273
  • Abstract
    Multiuser orthogonal frequency division multiplexing (MU-OFDM) is a promising technique for achieving high downlink capacities in future cellular and wireless local area network systems. The capacity of MU-OFDM can be maximized as long as subchannels and power are allocated adaptively, a new method based on genetic algorithm (GA) is proposed for adaptive power allocation in MU-OFDM system. Some proportional fairness constraints are also added to assure that each user can achieve a required data rate. Each subchannel to the user with the best channel-to-noise ratio has been assigned and an optimal power allocation algorithm based on GA has been proposed. The results demonstrate that the new method we proposed is optimal and efficient to resource allocation.
  • Keywords
    OFDM modulation; genetic algorithms; multi-access systems; resource allocation; wireless channels; adaptive power allocation; adaptive resource allocation; cellular systems; channel-to-noise ratio; genetic algorithm; high downlink capacities; multiuser OFDM system; orthogonal frequency division multiplexing; proportional fairness constraints; wireless local area network systems; Bit error rate; Computer networks; Constraint optimization; Downlink; Genetic algorithms; Information science; Mobile communication; Mobile computing; OFDM modulation; Resource management; GA; MU-OFDM; resource allocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications and Mobile Computing, 2009. CMC '09. WRI International Conference on
  • Conference_Location
    Yunnan
  • Print_ISBN
    978-0-7695-3501-2
  • Type

    conf

  • DOI
    10.1109/CMC.2009.269
  • Filename
    4796999