Random Vector Differential Entropy Based Cognitive Radio Spectrum Sensing

Conference: European Wireless 2015 - 21th European Wireless Conference
05/20/2015 - 05/22/2015 at Budapest, Hungary

Proceedings: European Wireless 2015

Pages: 6Language: englishTyp: PDF

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Mohamad, Usama Y.; Dahlhaus, Dirk (Communications Laboratory, University of Kassel, Germany)

Spectrum sensing in cognitive radio systems is a substantial component to explore the spectral holes for subsequent transmission. The differential entropy has gained great attention in several information theoretic contexts, but considerably less in signal processing applications. A novel sensing algorithm for detecting the presence of a primary user signal in a multiple antenna system is presented in this paper. The scheme employs the entropy estimate of the received frame to accomplish the sensing task. Different entropy estimators are used and compared in terms of their probability of error in both Bayesian and Neyman Pearson testing. It turns out that the resulting performance of the kth nearest neighbor estimator based detection scheme is close to the one of the optimal detector, namely, the estimatorcorrelator, but with less required information. Moreover, the proposed algorithms can handle any distribution of the received signal and thus be considered an extension of the Gaussian signal case.