An Improved Cluster-Based Cooperative Spectrum Sensing Algorithm

These instructions give you basic guidelines for preparing camera-ready papers for AP’s journals In the traditional cluster-based collaboration spectrum sensing algorithm, judgment threshold is only related to the false alarm probability. Besides, the cluster head use a simple OR-rule to execute information fusion, which limits the sensing performance to some extent. In this thesis, we propose an improved cluster-based cooperative spectrum sensing algorithm. The judgment thresholds are adjusted based on channel conditions, which can improve the local sensing performance. The cluster head use the half-weighted fusion rule 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 algorithm can improve the spectrum sensing performance than the traditional algorithm through analyzing and simulating.