• DocumentCode
    2055456
  • Title

    Probabilities of detection and false alarm in multitaper based spectrum sensing for cognitive radio systems in AWGN

  • Author

    Alghamdi, O.A. ; Ahmed, M.Z. ; Abu-Rgheff, Mosa Ali

  • Author_Institution
    Mobile Commun. Res. Group, Univ. of Plymouth, Plymouth, UK
  • fYear
    2010
  • fDate
    17-19 Nov. 2010
  • Firstpage
    579
  • Lastpage
    584
  • Abstract
    The paper presents closed-form expressions for the detection, and false alarm probabilities for spectrum sensing detection in Additive White Gaussian Noise (AWGN) based on the Multitaper Spectrum Estimation Method (MTM) using Neyman-Pearson criterion. The MTM spectrum sensing is a powerful technique in Cognitive Radio (CR) systems. It tolerates problems related to bad biasing, and large variance of estimates, that are the main drawbacks in the periodogram (energy detector). The performance of the MTM spectrum sensing system is controlled by parameters, such as the chosen half time bandwidth product, Discrete Prolate Slepian Sequence (DPSS) (i.e., tapers), DPSS´ eigenvalues, and the number of tapers used. These parameters determine the theoretical probabilities of detection and false alarms, which are used to evaluate the system performance. The paper shows a good match between the theoretical and numerical simulation results.
  • Keywords
    AWGN; cognitive radio; AWGN; CR system; DPSS eigenvalues; MTM spectrum sensing; Neyman-Pearson criterion; additive white Gaussian noise; cognitive radio system; discrete prolate slepian sequence; false alarm multitaper spectrum estimation method sensing; AWGN; Detectors; OFDM; Probability; Signal to noise ratio; cognitive radio; multitaper spectrum estimation; spectrum sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Systems (ICCS), 2010 IEEE International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-7004-4
  • Type

    conf

  • DOI
    10.1109/ICCS.2010.5686717
  • Filename
    5686717