Sensing-Throughput Tradeoff in Cluster-Based Cooperative Cognitive Radio Networks: A Novel Frame Structure

Abstract

In cooperative cognitive radio networks (CCRNs), the reporting time is consumed by all secondary users (SUs) for reporting the sensing results to the central node or fusion center. Intuitively, the performance of CCRNs will be degradation, since the more SUs for cooperation, the more reporting time for reporting sensing results. However, most previous studies have not considered this point. In this paper, a cluster-based cooperative spectrum sensing model is proposed in order to reduce the reporting time. Based on a novel frame structure, a sensing-throughput tradeoff problem considering the reporting time is formulated for two scenarios. The optimal clustering rule is obtained by maximizing the transmission time of all SUs. Then, a low-complexity solution is proposed to solve the tradeoff problem, which shows close-to-optimal performance by simulation.