Research On Cooperative Spectrum Sesing In Cognitive Radio Networks

The spectrum suitable to communicate is became exhausting accompany with the growth wireless applications. Cognitive radio provides a new way to use the spectrum resources better. Cognitive radio is a intelligent wireless communications system which can be aware of the environment around it and adjust its parameters according to the sensing results. It can take full advantage of the spectrum resources to improve the spectrum utilization. In the cognitive radio system, the secondary users can access the authorized spectrum opportunistically, and should be able to vacate the frequency bands quickly whenever one or more primary users return to avoid interference to primary users. Therefore, the reliable spectrum sensing technology is needed. Collaborative spectrum sensing is receiving more and more concern recently for it can provide more detection accuracy.This thesis mainly focus on the collaborative spectrum sensing technology in cognitive radio networks. There are usually many sensing users in cooperative sensing networks which inevitably result in a large sensing latency. To improve the problem, we proposed a cooperative sensing time optimization algorithm. The algorithm can decrease the sensing overhead thorough arranging proper number of users with the guarantee of probability of detection and false alarm probability. In cognitive radio systems, the sensing system and transmission system are generally designed separately which is simple and easy to implement, but cannot achieve the best performance. To solve the problem, this paper propose a algorithm that jointly optimize the two systems. In the cooperative stage, sensing users will send their sensing results to each other, and fuse the results using OR rule to improve sensing performance. In the transmission phase, users relay others'signal to improve transmission capacity. The equation of system throughput is obtained in this paper. We optimize the system with the goal of throughput maximization. To get the optimize point rapidly, an iterative search algorithm is proposed.