Presentation 2012-03-07
Spectrum Sensing Algorithms via Finite Random Matrix Theory
Wensheng ZHANG, Giuseppe ABREU, Mamiko INAMORI, Yukitoshi SANADA,
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Abstract(in English) We address the Primary User (PU) detection (spectrum sensing) problem, relevant to cognitive radio, from a finite random matrix theoretical (RMT) perspective. Specifically, we employ recently-derived closed-form and exact expressions for the distribution of the standard condition number (SCN) of uncorrelated and semi-correlated random dual central Wishart matrices of finite sizes in the design Hypothesis-Testing algorithms to detect the presence of PU signals. In particular, the algorithms are designed with basis on the SCN distribution in the absence (H_0) and in the presence (H_1) of PU signals, respectively. Due to an inherent property of the SCN's, the Ho test requires no estimation of SNR or any other information on the PU signal, while the H_1 test requires SNR only. It is also shown that the proposed finite RMT-based algorithms outperforms all similar alternatives currently known in the literature, at a substantially lower complexity.
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Keyword(in English) Cognitive Radio / Spectrum Sensing / Random Matrix / Standard Condition Number / Hypothesis Test
Paper # SR2011-112
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Conference Date 2012/2/29(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Spectrum Sensing Algorithms via Finite Random Matrix Theory
Sub Title (in English)
Keyword(1) Cognitive Radio
Keyword(2) Spectrum Sensing
Keyword(3) Random Matrix
Keyword(4) Standard Condition Number
Keyword(5) Hypothesis Test
1st Author's Name Wensheng ZHANG
1st Author's Affiliation Dept. of Electronics and Electrical Engineering, Keio University()
2nd Author's Name Giuseppe ABREU
2nd Author's Affiliation Centre for Wireless Communications, University of Oulu
3rd Author's Name Mamiko INAMORI
3rd Author's Affiliation Dept. of Electronics and Electrical Engineering, Keio University
4th Author's Name Yukitoshi SANADA
4th Author's Affiliation Dept. of Electronics and Electrical Engineering, Keio University
Date 2012-03-07
Paper # SR2011-112
Volume (vol) vol.111
Number (no) 452
Page pp.pp.-
#Pages 7
Date of Issue