Optimization of Cooperative Spectrum Sensing in Multiple-Channel Cognitive Radio Networks

Cooperative spectrum sensing (CSS) is a promising technology in cognitive radio (CR) networks. Among the many existing CSS methods, the cooperation in a single channel is studied extensively. However, CR networks usually deal with multiple channels, therefore multi-channel CSS needs be studied. In this paper, we investigate the problems that how to optimally assign secondary users (SU) to cooperatively sense multiple channels and how to optimally set the sensing time and sensing thresholds. An optimization problem of multi-channel CSS is formulated to maximize the average throughput of CR networks subject to the constraints of probability of detection for each channel. An exhaustive algorithm and a greedy algorithm are proposed to obtain the optimal solutions of the optimization problem. Finally, both analytical and numerical results are presented to demonstrate the effectiveness of our proposed algorithms. It is also shown that the greedy algorithm with a low complexity achieves the same performance as the exhaustive algorithm.