• DocumentCode
    2092383
  • Title

    Optimal threshold and weighted cooperative data combining rule in Cognitive Radio network

  • Author

    Zhai Xuping ; Haigen, He ; Guoxin, Zheng

  • Author_Institution
    Key Lab. of Specialty Fiber Opt. & Opt. Access Networks, Shanghai Univ., Shanghai, China
  • fYear
    2010
  • fDate
    11-14 Nov. 2010
  • Firstpage
    1464
  • Lastpage
    1467
  • Abstract
    This work was supported by following projects: Shanghai Leading Academic Discipline Project (S30108), STCSM (08DZ2231100) and the National Natural Science Foundation of China (60872021). Abstract-For spectrum sensing in Cognitive Radio (CR), previous researches mostly considered that distributed CR nodes are under identical channel conditions, so uniform and fixed detection threshold is set normally with Energy Detector. However, the distribution of nodes is not quite the same due to different channel states. In this paper, the optimal threshold to minimize the total error rate over AWGN channel is derived firstly. Then the effect of variable SNR and noise power on the optimal threshold is investigated. Based upon the optimal threshold theory, we propose Dynamic Threshold Scheme to reduce average total error rate for local CR node. Finally, for cooperative sensing, to distinguish the role of different nodes at Base Station, weighted rule for data combining, based on the difference between energy decision statistic and the optimal threshold, is proposed. Simulations have shown the performance is conditionally improved a lot compared with other rules.
  • Keywords
    AWGN channels; cognitive radio; AWGN channel; cognitive radio network; optimal threshold; total error rate; weighted cooperative data combining rule;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Technology (ICCT), 2010 12th IEEE International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-6868-3
  • Type

    conf

  • DOI
    10.1109/ICCT.2010.5688975
  • Filename
    5688975