NDLI: P-GLRT Algorithm for Cooperative Spectrum Sensing

Content Provider	Springer Nature Link
Author	Liu, Fulai Du, Ruiyan Guo, Junping Guo, Shouming
Copyright Year	2014
Abstract	Spectrum sensing is a crucial task for a cognitive radio system. It enables cognitive radio to identify vacant frequency bands and to opportunistically access spectrum. Thus, reliable detection of primary users is important since the cognitive radio (CR) operating as a secondary system is not allowed to cause harmful interference to PUs. In this paper, an effective generalized likelihood ratio test (GLRT) based on power method (named as P-GLRT algorithm) is proposed for cooperative spectrum sensing. Compared with the previous works, the presented method offers a number of advantages over other recently proposed algorithms. Firstly, it can solve the problem of uncertain noise and lower signal-to-noise ratio. Secondly, it requires no prior knowledge of the transmitted signal, the wireless channel gains from the primary transmitter to the CR receiver, and the noise variance. Finally, the proposed approach makes use of power method to obtain the maximum eigenvalue and the corresponding eigenvector for maximum likelihood estimates of unknown parameters, it avoids the eigenvalue decomposition processing. Simulation results show the proposed algorithm has better detection performance than other relevant methods. Meanwhile, some performance analysis of the proposed algorithm via simulations are presented.
Starting Page	1079
Ending Page	1089
Page Count	11
File Format	PDF
ISSN	09296212
Journal	Wireless Personal Communications
Volume Number	81
Issue Number	3
e-ISSN	1572834X
Language	English
Publisher	Springer US
Publisher Date	2014-11-09
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Cognitive radio network Spectrum sensing Power method Generalized likelihood ratio test Communications Engineering, Networks Signal, Image and Speech Processing Computer Communication Networks
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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