Feasibility of maximum eigenvalue cooperative spectrum sensing based on Cholesky factorisation

Abstract

An efficient cooperative spectrum sensing (SS) scheme based on Cholesky decomposition of the covariance matrix is proposed. The maximum eigenvalue (ME) of the matrix obtained by Cholesky decomposition is used as a test statistic. Analytical expressions for the false alarm probability and the decision threshold are derived. The effects of noise uncertainty on the ME SS algorithm and on the Cholesky ME cooperative SS scheme are assessed. It is proved that the proposed SS scheme is more robust than the conventional ME SS scheme in terms of noise uncertainty. Simulation results show that the performance of the proposed scheme is better than that of existing ME SS scheme in some conditions.