Detection Performance of Cooperative Spectrum Sensing with Hard Decision Fusion in Fading Channels

In this paper, we investigate the detection performance of cooperative spectrum sensing (CSS) using energy detector (ED) in several fading scenarios. The fading environments comprises of relatively less-studied Hoyt and Weibull channels in addition to the conventional Rayleigh, Rician, Nakagami-m, and log-normal shadowing channels. We have presented an analytical framework for evaluating different probabilities related to spectrum sensing, i.e. missed detection, false alarm, and total error due to both of them, for all the fading/ shadowing models mentioned. The major theoretical contribution is, however, the derivation of closed-form expressions for probability of detection. Based on our developed framework, we present performance results of CSS under various hard decision fusion strategies such as OR rule, AND rule, and Majority rule. Effects of sensing channel signal to noise ratio (SNR), detection threshold, fusion rules, number of cooperating CRs, and fading/ shadowing parameters on the sensing performance have been illustrated. The performance improvement achieved with CSS over a single CR based sensing is depicted in terms of total error probability. Further, an optimal threshold that minimizes total error probability has been indicated for all the fading/ shadowing channels.