• DocumentCode
    3603845
  • Title

    An Accurate Kernelized Energy Detection in Gaussian and non-Gaussian/Impulsive Noises

  • Author

    Margoosian, Argin ; Abouei, Jamshid ; Plataniotis, Konstantinos N.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Yazd Univ., Yazd, Iran
  • Volume
    63
  • Issue
    21
  • fYear
    2015
  • Firstpage
    5621
  • Lastpage
    5636
  • Abstract
    Motivated by the simplicity of energy detector and capability of higher order and fractional lower order statistics in non-Gaussian signal processing, this paper proposes a new spectrum sensing method based on kernel theory, referred to as Kerenlized Energy Detector (KED), which exhibits a moderate complexity, it is easy to implement, and it compares favourably against competing solutions in the case of various Gaussian and non-Gaussian impulsive noises. The incorporation of the nonlinear kernel function in the KED test statistic allows for the development of a nonlinear algorithm capable of considering both higher order and fractional lower order moments (FLOMs) in the sensing task. We show that the proposed KED detector can serve as an optimal spectrum sensing method under both Gaussian and non-Gaussian noise scenarios. In addition, the detection performance of the proposed KED scheme is analyzed by employing U-statistics theory. The Kernel parameter selection for the KED method has been discussed in both theoretical and practical points of view. Potential of considering the KED scheme in either single user multi-antennas or cooperative spectrum sensing is investigated.
  • Keywords
    Gaussian noise; antenna arrays; cooperative communication; higher order statistics; impulse noise; radio spectrum management; signal detection; statistical testing; FLOM; Gaussian impulsive noise; KED test statistic; U-statistics theory; cooperative spectrum sensing method; energy detector; fractional lower order statistics capability; higher order statistics capability; kernel theory; kernelized energy detection; nonGaussian impulsive noise; nonGaussian signal processing; nonlinear kernel function; single user multiantennas; Computational complexity; Detectors; Kernel; Laplace equations; Noise; Signal processing algorithms; $alpha$ -stable noise model; Cognitive radio; U-statistics; kernel theory; non-Gaussian impulsive noises; spectrum sensing;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2015.2457400
  • Filename
    7161400