Weighted cooperative spectrum sensing algorithm based on improved energy detection

The single-node energy detection has the drawbacks of low detection accuracy andhidden terminalwhile coopera- tive sensing algorithms usually use equivalent weights for data fusion instead of considering the influence to the detection perfor- mance resulting from communication environment of different nodes. In order to solve the above problems, this paper proposes an adaptive weighted cooperative spectrum sensing algorithm based on improved energy detection which improves single node energy detection and derives the relationship between Signal-to-Noise Ratio(SNR)and decision threshold under the condition of minimal error probability. This paper adopts dichotomy to get dynamic threshold values and corresponding false probability and detection probability at different SNR. It regards the function of false probability and detection probability as the weighted factor to do data fusion. The simulation results show that the proposed algorithm can achieve reliable detection performance of cooperative sensing system with low SNR.