Cooperative Spectrum Sensing Algorithm Based on Vote Fusion under Bandwidth Constraints

Cooperative spectrum sensing enables a Cognitive Radio (CR) networks to reliably detect primary users and avoid causing interference to primary user’s communications. The data fusion technique is a key component of cooperative spectrum sensing. However when the number of Cognitive Radio users tends to be very large, the bandwidth for reporting sensing results of the all users to the fusion center will be extremely huge. In this paper, a censoring scheme based on vote fusion rule for cooperative spectrum sensing is proposed to decrease the average number of sensing bits to the fusion center. Consequently, the bandwidth is saved efficiently using this method. The performance of spectrum sensing is investigated for both perfect reporting channels and imperfect reporting channels, and the close formulations of the detection probability are presented. Simulation results show that the performance of the censoring scheme based on vote fusion rule for cooperative spectrum sensing is optimal. It means that the average number of sensing bits decreases greatly with fine sensing performance.