Analysis and optimization of Centralized Sequential Channel Sensing in Cognitive Radio Networks

Effective spectrum sensing strategies enable cognitive radios to enhance the spectrum efficiency. In this paper, modeling, performance analysis, and optimization of spectrum handoff in a centralized cognitive radio network are studied. More specifically, for a given sensing order, the average throughput of secondary users and average interference level among the secondary and primary users are evaluated for a cognitive radio network with only one secondary user. By a Markov chain analysis, a network with multiple secondary users performing cooperative spectrum sensing is modeled, and the above performance metrics are derived. Then, a maximization of the secondary network performance in terms of throughput while keeping under control the average interference is formulated. Finally, numerical results validate the analytical derivations and show that optimally tuning sensing time significantly enhances the performance of the spectrum handoff. Also, we observe that exploiting OR rule for cooperative spectrum sensing provides a higher average throughput compared to AND rule.