An Enhanced Covariance Spectrum Sensing Technique Based on Stochastic Resonance in Cognitive Radio Networks

In this paper, a novel covariance spectrum sensing approach used in cognitive radio (CR) networks which is based on the dynamical stochastic resonance (SR) technique is proposed. When the optimal SR technique is introduced as the pre-processing method for the covariance-based detection and after it has been realized, it can increase the signal-to-noise ratio (SNR) of the primary user (PU) signal and accordingly increase the mean value of the decision statistic of the covariance-based detection, so that the detection probability of the proposed approach can be improved under constant false alarm rate (CFAR). Computer simulation results verify the effectiveness of the proposed approach compared with the traditional spectrum sensing methods.