NDLI: An efficient spectrum sensing algorithm for cognitive radio based on finite random matrix

Content Provider	IEEE Xplore Digital Library
Author	Fuhui Zhou Zan Li Jiangbo Si Lei Guan
Copyright Year	2014
Description	Author affiliation: State Key Lab. of Integrated Services Networks, Xidian Univ., Xi'an, China (Fuhui Zhou; Zan Li; Jiangbo Si; Lei Guan)
Abstract	Spectrum sensing is the precondition of implementation of cognitive radio. Motivated by the fact that eigenvalue detection algorithms are based on eigenvalue decomposition over the covariance matrix, we propose an efficient spectrum sensing algorithm based on Cholesky decomposition over that matrix. Using eigenvalues of the matrix which is obtained by Cholesky decomposition over finite covariance matrix, the efficient spectrum sensing algorithm is proposed. Attractive advantages of our proposed technique are: a) no assumptions on the sampling size and the dimension of the random matrix are required; b) exact and simple closed-form analytical expressions for the false alarm probability and decision threshold are derived under practical scenarios of finite size of the covariance matrix and samples; c) numerical simulations show that the presented algorithm achieves performance improvement compared with previous algorithms based on eigenvalue.
Starting Page	1223
Ending Page	1227
File Size	160819
Page Count	5
File Format	PDF
ISBN	9781479949120
DOI	10.1109/PIMRC.2014.7136354
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-02
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Covariance matrices Sensors Eigenvalues and eigenfunctions Approximation algorithms Cognitive radio Matrix decomposition Algorithm design and analysis matrix decomposition Cognitive radios spectrum sensing random matrix theory
Content Type	Text
Resource Type	Article

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