As a smart combination of cognitive radio networks and wireless sensor networks,recently introduced cognitive radio sensor network(CRSN) poses new challenges to the design of topology maintenance techniques for dynamic primary-user activities.This paper aims to provide a solution to the energy-efficient spectrum-aware CRSN clustering problem.Specifically,we design the clustered structure,establish a network-wide energy consumption model and determine the optimal number of clusters.We then employ the ideas from constrained clustering and propose both a centralized spectrum-aware clustering algorithm and a distributed spectrum-aware clustering(DSAC) protocol.Through extensive simulations,we demonstrate that DSAC can effectively form clusters under a dynamic spectrum-aware constraint.Moreover,DSAC exhibits preferable scalability and stability with its low complexity and quick convergence under dynamic spectrum variation.
We propose a reputation-based cooperative spectrum sensing scheme in cognitive radio (CR) networks to solve the uncertainty resulting from the multipath fading and shadowing effect. In the proposed scheme, each cooperative CR user has a reputation degree that is initialized and adjusted by the central controller, and used to weight the sensing result from the corresponding CR user in the linear fusion process at the central controller. A simple method for adjusting the reputation degree of CR users is also presented. We analyzed and evaluated the detection performance of the reputation-based cooperative spectrum sensing scheme. Simulation results showed that our proposed scheme alleviates the problem of corrupted detection resulting from destructive channel conditions between the primary transmitter and the CR user. The performance of our proposed scheme was improved compared to the average-based linear cooperation scheme, and was similar to that of the optimal linear cooperation scheme with feasible computational complexity. Moreover, our proposed scheme does not require knowledge of channel statistics.
