Research Onspectrum Sensing Algorithm In Cognitive Radio

With the rapid development of wireless communications,the conflict between the supply and demand of spectrum resources has become more and more serious. Cognitive radio can take full advantage of the existing spectrum resources. Spectrum sensing technology is the key in the cognitive radio, by which we can find vacant spectrum and sense the re-emergence of the primary user. This thesis introduces the existing spectrum sensing technology fully.In this thesis, we propose an improved double-threshold collaborative spectrum sensing method. By discriminating the influence of different cognitive user on the soft fusion result and the hard decision result, we can reduce the influence to the final result for the poor cognitive user and improve the influence to final result for the good cognitive user, which can improve the accuracy of the final result, and then improve the overall spectrum sensing performance. Finally, we verify that this improved algorithm has better performance than the traditional algorithm through analyzing and simulating.In traditional cluster-based cooperative spectrum sensing method, the cognitive users in cluster use the decision threshold which is only related to the probability of false alarm to execute the local detection, and the cluster head use the OR criteria to execute the information fusion, which limit the spectrum detection performance to some extent. Therefore, in order to improve the detection performance further, in this thesis, while executing the local detection, we can adjust the decision threshold according to the perceived channel conditions between the primary user and the cognitive user respectively, and then perform the local judgment. The cluster head use the half-weighted fusion rule which is proposed in this thesis to execute the information fusion, by which the cluster head can treat their detection results based on the different reliability of the cognitive users. Finally, we verify that this improved scheme can improve the detection probability than the traditional scheme through analyzing and simulating, thereby enhance the spectrum sensing performance.