• DocumentCode
    2041772
  • Title

    Multi-bit cooperative spectrum sensing strategy in closed form

  • Author

    Xiaoyuan Fan ; Dongliang Duan ; Liuqing Yang

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Wyoming, Laramie, WY, USA
  • fYear
    2013
  • fDate
    3-6 Nov. 2013
  • Firstpage
    1473
  • Lastpage
    1477
  • Abstract
    Spectrum sensing is one of the most important tasks in cognitive radio system. In order to combat fading, cooperation among different sensing users is usually adopted. In our previous work [1], we quantified the performance gain of cooperative spectrum sensing by the notion of diversity. In addition, we have shown that even with local binary decisions, the cooperative spectrum sensing can achieve the maximum diversity by appropriately selecting local and fusion rules. However, there is a significant signal-to-noise ratio (SNR) loss compared with the soft information fusion scenario due to local binary quantization. Intuitively, increasing the number of bits of local quantization will improve the sensing performance. Most work in the literature on multi-bit cooperative sensing are mathematically intractable and can only be solved numerically with high complexity. In this paper, by jointly maximizing diversity and SNR gain, we provide a generalized multi-bit cooperative sensing strategy with the local and fusion decision rules in explicit closed form. Simulations show that even with small number of bits, our proposed cooperative sensing strategy can significantly improve the sensing performance.
  • Keywords
    binary decision diagrams; cognitive radio; cooperative communication; diversity reception; radio spectrum management; signal detection; SNR gain; SNR loss; cognitive radio system; fusion decision rules; local binary decisions; local binary quantization; local decision rules; maximum diversity; multibit cooperative spectrum sensing strategy; sensing performance; signal-to-noise ratio; soft information fusion scenario; Cognitive radio; Error probability; Fading; Gain; Quantization (signal); Sensors; Signal to noise ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 2013 Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA
  • Print_ISBN
    978-1-4799-2388-5
  • Type

    conf

  • DOI
    10.1109/ACSSC.2013.6810540
  • Filename
    6810540