| Cognitive radio is an intelligent communication system which can sense the communication environment around and change the correlative parameters of system rapidly. Spectrum sensing of high reliability is one of the key technologies to achieving spectrum sharing. The thesis mainly researches cooperative spectrum sensing and decision fusion algorithm in cognitive radio.Firstly, this paper analyses the developing summary of cognitive radio and the existing investigation about spectrum sensing technology. And then, several typical detection methods of individual node are described and compared primarily. In order to deal with this limitation of individual node, cooperative spectrum sensing is introduced. It is proved cooperative spectrum sensing is effective under Additive White Gaussian Noise and Rayleigh channel by simulation.Several conventional soft decision methods and hard decision methods in cooperative spectrum sensing are discussed and compared in the thesis. Furthermore, it finds the optimal fusion rule and the optimal threshold by simulation through investigating the optimal algorithm under each node with same Signal to Noise Ratio. And then, we propose two improved schemes under each node with different Signal to Noise Ratio on cluster-based cooperative spectrum sensing algorithm. Simulation results show the improved schemes have better detection probability. Finally, through analyzing the effect of individual node spectrum sensing and multi-nodes spectrum sensing under different Signal to Noise Ratio, we propose a distributed cooperative spectrum sensing algorithm based on K out of N rule in this paper. Based on the Signal to Noise Ratio comparison, the nodes chose to participate in fusion center adopt K out of N rule. Simulation results show the proposed algorithm improves the detection probability of cognitive users compared to adopted OR rule in literature. Meanwhile, the nodes not to participate in fusion center need not to local spectrum sensing. |
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