Cluster-Based Cooperative Spectrum Sensing in Cognitive Radio Systems

In cognitive radio systems, secondary users can be coordinated to perform cooperative spectrum sensing so as to detect the primary user more accurately. However, when the sensing observations are forwarded to a common receiver through fading channels, the sensing performance can be severely degraded. In this paper, we propose a cluster-based cooperative spectrum sensing method to improve the sensing performance. By separating all the secondary users into a few clusters and selecting the most favorable user in each cluster to report to the common receiver, the proposed method can exploit the user selection diversity so that the sensing performance can be enhanced. Furthermore, decision fusion and energy fusion are both studied and the analytical performance results are given. Numerical results show that the sensing performance is improved significantly as opposed to conventional spectrum sensing.