Abstract: A novel maximum eigenvalue-harmonic mean (NMEHM) blind spectrum sensing algorithm is proposed,using the results of the distribution of the limiting eigenvalues of the sample covariance matrix in random matrix theory.The proposed algorithm significantly improves the detection performance of the traditional MEHM algorithm and achieves better detection performance than the classical eigenvalues-based detection algorithms;at the same time,the proposed algorithm does not require a priori knowledge of the primary user signal and wireless channel,which can availably overcome the effect of noise uncertainty.Simulation results demonstrate the validity of the proposed algorithm.

Key words: spectrum sensing, random matrix theory, eigenvalue, sample covariance matrix, harmonic mean