Double Threshold Based Weighted-Clustering Cooperative Spectrum Sensing Algorithm in Cognitive Radio Networks

cognitive radio systems, cooperative spectrum sensing has been widely used to detect the primary user with a high agility and accuracy. However, the limitation of control channel bandwidth is a challenge of cooperative spectrum sensing when the number of cognitive users becomes very large. In this paper, weighted-clustering architecture is applied for cooperative sensing to avoid the congestion on the control channel and reduce the sensing delay. A double threshold based weighted-clustering cooperative spectrum sensing algorithm in Rayleigh channel is proposed to improve the detection performance and reduce transmitting overhead. Computer simulations show that the sensing performance is improved significantly as opposed to conventional sensing algorithm.