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http://dx.doi.org/10.3837/tiis.2019.09.003

Complexity based Sensing Strategy for Spectrum Sensing in Cognitive Radio Networks  

Huang, Kewen (School of physics and mechanics, Shaoguan University)
Liu, Yimin (School of physics and mechanics, Shaoguan University)
Hong, Yuanquan (School of physics and mechanics, Shaoguan University)
Mu, Junsheng (School of information and communication, Beijing University of Posts and Telecommunications)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.13, no.9, 2019 , pp. 4372-4389 More about this Journal
Abstract
Spectrum sensing has attracted much attention due to its significant contribution to idle spectrum detection in Cognitive Radio Networks. However, specialized discussion is on complexity-based sensing strategy for spectrum sensing seldom considered. Motivated by this, this paper is devoted to complexity-based sensing strategy for spectrum sensing. Firstly, three efficiency functions are defined to estimate sensing efficiency of a spectrum scheme. Then a novel sensing strategy is proposed given sensing performance and computational complexity. After that, the proposed sensing strategy is extended to energy detector, Cyclostationary feature detector, covariance matrix detector and cooperative spectrum detector. The proposed sensing strategy provides a novel insight into sensing performance estimation for its consideration of both sensing capacity and sensing complexity. Simulations analyze three efficiency functions and optimal sensing strategy of energy detector, Cyclostationary feature detector and covariance matrix detector.
Keywords
Cognitive Radio Networks; spectrum sensing; sensing strategy; computational complexity;
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