On Signal Detection in the Presence of Weakly Correlated Noise over Fading Channels

In cognitive radio networks, in order to avoid interference form secondary users to the primary license holders of the spectrum, reliable spectrum sensing is necessary. In scenarios where the noise samples are correlated, the spectrum sensing methods optimized considering impairment by independent noise samples will not provide optimum performances. To address this issue, a locally optimum detection method for random signals under a weakly correlated noise model over fading channels is proposed. The probabilities of false alarm and detection of the proposed detector in the low signal to noise ratio regime are analyzed. The average probabilities are calculated over different channel gains. Numerical and simulation results demonstrate the superiority of the proposed method over the known energy detection method with comparable complexities. Furthermore, we consider the scenario where the estimated correlation is different from the real correlation and investigate the effect of this correlation mismatch on the probabilities of false alarm and detection of the proposed method.