The Research Of The Optimization Of Cooperative Spectrum Sensing In Cognitive Radio

With the rapid expansion of wireless communication, the wireless spectrum resources are becoming more and more precious. Fortunately, cognitive radio can solve this problem through which cognitive user can use the spectrum unoccupied by primary user and increase the utilization rate of spectrum resources. As the critical technology of cognitive radio, spectrum sensing methods can be divided into single node sensing and cooperative sensing. Cooperative sensing can solve the hidden terminal problem in spectrum sensing and it can get a better sensing performance compared with single node sensing. With these advantages above, cooperative sensing is widely studied.The research background and the current research status of cognitive radio are introduced firstly. Fusion method and the optimization strategy of cooperative sensing is summarized in this paper. Then two optimized strategies of cooperative sensing based on double-threshold detection are proposed.Based on traditional double-threshold detection cooperative sensing method, an optimized strategy is proposed in this paper in consideration of all sensing nodes fail to send their local decisions to the fusion center. Theoretical analysis and simulation results show that, compared with the traditional double-threshold detection method, optimized strategy proposed in this paper can have a better detection performance with smaller communication flow during cooperative sensing. Besides, the higher the probability of the sensing energy of the sensing nodes falls into the no-judge region, the better performance the optimized strategy will get compared with traditional double-threshold detection method. Besides, a cost formula of the double-threshold cooperative sensing is proposed in this paper. And simulation results show that, with a fixed number of sensing nodes in the cognitive sensing system, there must be an optimum number of sensing nodes to make the cost formula achieve its minimum value.A weighted-based algorithm is proposed in this paper based on double-threshold detection. During spectrum sensing, the fusion center allocates weight to each node dynamically according to the proposed algorithm, and then make the final decision according to the weight of each node. Simulation results show that when sensing efficiency of each node is different from each other, algorithm proposed in this paper can improve the detection performance greatly with smaller communication flow.