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
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