Developing an effective cooperative spectrum sensing (CSS) scheme in cognitive radio (CR), which is considered as\r\npromising system for enhancing spectrum utilization, is necessary. In this paper, a cluster-based optimal selective CSS\r\nscheme is proposed for reducing reporting time and bandwidth while maintaining a certain level of sensing\r\nperformance. Clusters are organized based on the identification of primary signal signal-to-noise ratio value, and the\r\ncluster head in each cluster is dynamically chosen according to the sensing data qualities of CR users. The cluster\r\nsensing decision is made based on an optimal threshold for selective CSS which minimizes the probability of sensing\r\nerror. A parallel reporting mechanism based on frequency division is proposed to considerably reduce the time for\r\nreporting decision to fusion center of clusters. In the fusion center, the optimal Chair-Vashney rule is utilized to obtain\r\na high sensing performance based on the available cluster�s information.
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