Spectrum sensing scheme based on random matrix theory

Spectrum sensing is the key technology in enabling spectrum awareness in cognitive radio. The performance of the spectrum sensing depends on the sensing method. In this paper, by means of random matrix theory (RMT), a novel spectrum sensing scheme and a threshold decision rule are proposed based on the difference between the maximum and the minimum eigenvalue (DMM) cooperative spectrum sensing algorithm, analyzing the minimum eigenvalue limiting distribution of the covariance matrix of the received signals from multiple cognitive users(CUs). The proposed scheme can overcome the noise uncertainty and need nothing about prior knowledge of the signal transmitted from the primary user (PU). Simulation results show that the proposed scheme outperforms DMM under lower signal-to-noise ratio (SNR) and smaller samples.