• DocumentCode
    655354
  • Title

    Optimization of Cooperative Spectrum Sensing under AWGN and Rayleigh Channels in Cognitive Radio Network

  • Author

    Reddy, G. Vidyadhar ; Murthy, N.S.

  • Author_Institution
    Nat. Inst. of Technol., Warangal, India
  • fYear
    2013
  • fDate
    29-31 Aug. 2013
  • Firstpage
    126
  • Lastpage
    129
  • Abstract
    This paper deals with cooperative spectrum sensing (CSS) under AWGN and Rayleigh channels with energy detection as sensing technique for cognitive radio network (CRN). The performance of m-out-of-N voting rule, OR fusion logic and AND fusion logic rules under varying threshold is studied, appropriate range of thresholds over which particular fusion rule can be applied has been investigated. An optimum voting rule has been used for AWGN and Rayleigh channels with an aim to improve the performance for real time implementation. A generalized optimal voting rule is derived to minimize the number of cognitive radios (CRs) required to meet target error bound. Simulations are performed for both the channels and the results are found to be comparable with the analytical results. It is observed that 2CRs for Rayleigh channel and 5 CRs for AWGN channel gives minimum error in a CRN of 10 CRs.
  • Keywords
    AWGN channels; Rayleigh channels; cognitive radio; cooperative communication; AWGN channels; OR fusion logic; Rayleigh channels; cognitive Radio Network; cooperative spectrum sensing optimization; fusion logic rules; generalized optimal voting rule; particular fusion rule; target error bound; AWGN channels; Cascading style sheets; Cognitive radio; Optimization; Rayleigh channels; Sensors; Signal to noise ratio; AWGN channel; Cognitive radio; Cooperative spectrum sensing; Energy detection; Rayleigh channel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Computing and Communications (ICACC), 2013 Third International Conference on
  • Conference_Location
    Cochin
  • Type

    conf

  • DOI
    10.1109/ICACC.2013.32
  • Filename
    6686353