Fusion rule and cluster head selection scheme in cooperative spectrum sensing

Abstract

Cluster based cooperative spectrum sensing (CSS) in cognitive radio networks provides for reduced sensing error, reporting delays and improved energy efficiency, in a practical network. However, achieving these advantages depend on suitably selecting a cluster head and adopting an appropriate fusion rule. This work investigates a new hard decision fusion rule, which makes the cluster heads non-cooperative sensing result a necessary condition for cooperative decision making. The study also presents a comparative numerical study of three existing cluster head selection schemes with respect to their performance in CSS, under varying detection thresholds and cluster's heterogeneity. A robust and generalised cluster head selection scheme that overcomes the limitations of the existing schemes is thereafter proposed. The performance of the existing cluster head selection schemes depends on the distribution of secondary users relative to the primary user's position, and the detection threshold. Simulation results show that the proposed cluster head selection scheme can overcome the limitations of existing schemes. Furthermore, the hard decision fusion rule being proposed indicates improved performance compared with the OR rule in minimising the total error rate over Rayleigh fading channels.