• DocumentCode
    615783
  • Title

    Energy-efficient transmission with cooperative spectrum sensing in cognitive radio networks

  • Author

    Yan Gao ; Wenjun Xu ; Kewen Yang ; Kai Niu ; Jiaru Lin

  • Author_Institution
    Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2013
  • fDate
    7-10 April 2013
  • Firstpage
    7
  • Lastpage
    12
  • Abstract
    With the continuous growth of the wireless communication business, energy issues and environmental problems are becoming increasingly grim. Therefore, this paper investigates the energy efficient transmission scheme with cooperative sensing in cognitive radio networks, in which AND fusion rule is introduced to determine the presence of the primary user. It is proved that the energy efficiency is a quasi-concave function with sensing time when the number of cooperative users satisfies certain constraints. Aiming at maximizing the energy efficiency, the transmission power is selected at first, then a scheme of jointly optimizing sensing time, energy detector threshold and the number of cooperative users is proposed based on the related theory analysis. From the simulations, it can be found that the optimal sensing time is only about half of that consumed in single user sensing, and the proposed scheme has significant improvement in energy efficiency.
  • Keywords
    cognitive radio; cooperative communication; energy conservation; optimisation; radio spectrum management; AND fusion rule; cognitive radio network; cooperative spectrum sensing; cooperative user; energy efficient transmission scheme; energy issues; environmental problem; primary user; quasiconcave function; sensing time optimisation; wireless communication business; Cognitive radio; Detectors; Energy consumption; Linear programming; Signal to noise ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications and Networking Conference (WCNC), 2013 IEEE
  • Conference_Location
    Shanghai
  • ISSN
    1525-3511
  • Print_ISBN
    978-1-4673-5938-2
  • Electronic_ISBN
    1525-3511
  • Type

    conf

  • DOI
    10.1109/WCNC.2013.6554530
  • Filename
    6554530