Maximum channel throughput via cooperative spectrum sensing in cognitive radio networks

In cognitive radio networks, the secondary (unlicensed) users need to find idle channels via spectrum sensing for their transmission. Cooperative spectrum sensing (CSS) is a promising technology in spectrum sensing with an admirable performance. In CSS, multiple secondary users individually sense the idle channels and send their decisions to the network center, and then the center will do a final decision. In this paper, we focus on the optimal sensing settings of the CSS to maximize the channel throughput under some constraints on the interference to cognitive radio network. Particularly, we consider two scenarios in this paper. In the first scenario, only one channel is sensed at one time, and we aim at maximizing an individual channel capacity. Some simple algorithms are also derived to calculate the optimal solution for the first scenario. In the second scenario, multiple channels are jointly sensed simultaneously, and our objective is to maximize the overall channel capacity. We prove that the optimization problem in the second scenario can be converted into a convex-optimization problem, which can be solved efficiently and reliably. Simulation results show a significant improvement of the channel capacity by using the proposed optimal CSS in cognitive radio networks.