• DocumentCode
    1787268
  • Title

    Energy efficient sensor selection in multi-band cognitive sensor network

  • Author

    Avili, Morteza Ghomi ; Andargoli, Seyed Mehdi Hosseini

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Babol Noshirvani Univ. of Technol., Babol, Iran
  • fYear
    2014
  • fDate
    9-11 Sept. 2014
  • Firstpage
    1100
  • Lastpage
    1105
  • Abstract
    In this paper, we address the problem of sensor selection for energy efficient spectrum sensing in multi-band cognitive sensor networks. We formulate the problem of sensor selection in multi-band case in order to minimize energy consumption while satisfying the detection performance constraints. Energy detector is used as a simple detector which can be implemented in practice. Due to NP-hardness of the original problem, we relaxed it to a more tractable form and suboptimal solution is extracted based on convex optimization framework. Simulation results show that the proposed algorithm not only consumes the least energy in comparison with benchmark algorithms, but has the most ability in finding solutions which satisfy detection performance constraints.
  • Keywords
    cognitive radio; computational complexity; convex programming; energy conservation; telecommunication power management; wireless sensor networks; NP-hardness problem; convex optimization framework; energy consumption minimization; energy detector; energy efficient spectrum sensing; multiband cognitive sensor network; sensor selection; Benchmark testing; Cost function; Energy consumption; Energy efficiency; Sensors; Signal to noise ratio; Cognitive radio; cooperative spectrum sensing; detection and false alarm probabilities; fusion center; multi-band; wireless sensor network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Telecommunications (IST), 2014 7th International Symposium on
  • Conference_Location
    Tehran
  • Print_ISBN
    978-1-4799-5358-5
  • Type

    conf

  • DOI
    10.1109/ISTEL.2014.7000868
  • Filename
    7000868