Performance Analysis and Application of Exponential Weighted Collaborative Spectrum Sensing Scheme

This paper introduces a new weighted soft combination algorithm in order to further enhance the performance of collaborative spectrum sensing in cognitive radio network.The algorithm calculates weights by exponential form of signal to noise ratio,with the goal to reach better approximation of weights-SNR curve to probability of detection-SNR curve so as to better use SNR information to improve the performance of collaborative spectrum sensing.The idea and model of exponential weighted soft combination are introduced based on the sensing model.Based on energy detection,the paper simulates and compares the performances of this new algorithm and traditional soft combination algorithms in Rayleigh and Nakagami fading channel.Then the optimal threshold is obtained by analyzing of the algorithm.Finally,the new algorithm is applied to cluster-based collaborative spectrum sensing and is simulated for performance analysis.The results indicate that the proposed algorithm can effectively improve detection performance.