P-GLRT Algorithm for Cooperative Spectrum Sensing

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.