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Cooperative Bayesian Compressed Spectrum Sensing for Correlated Wideband Signals
Honggyu JUNG Kwang-Yul KIM Yoan SHIN
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2014/06/01
Online ISSN: 1745-1337
Type of Manuscript: LETTER
Category: Communication Theory and Signals
cognitive radio, spectrum sensing, compressed sensing, sparse Bayesian learning, multiple measurement vector,
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We propose a cooperative compressed spectrum sensing scheme for correlated signals in wideband cognitive radio networks. In order to design a reconstruction algorithm which accurately recover the wideband signals from the compressed samples in low SNR (Signal-to-Noise Ratio) environments, we consider the multiple measurement vector model exploiting a sequence of input signals and propose a cooperative sparse Bayesian learning algorithm which models the temporal correlation of the input signals. Simulation results show that the proposed scheme outperforms existing compressed sensing algorithms for low SNRs.