An Optimal Soft Fusion Scheme for Cooperative Spectrum Sensing in Cognitive Radio Network

This paper proposes an optimal soft fusion scheme for cooperative spectrum sensing in cognitive radio (CR) network. Multiple cooperative secondary users (SUs) simply serve as relay nodes in the network to provide space diversity for spectrum sensing. An optimal soft fusion scheme of the relayed sensing observations is derived in Neyman-Pearson framework, on the basis of maximizing the deflection coefficient of the global test statistic at the fusion center. However, the proposed fusion scheme requires instantaneous measurements of the received PU signal strengths in SUs with high accuracy, which are extremely difficult to obtain in an energy detection based spectrum sensing scenario. An iterative algorithm is therefore proposed to perform the estimation of the received PU signal strengths. Simulation results illustrate that the proposed optimal soft fusion scheme can significantly improve the spectrum sensing performance and the estimate algorithm can effectively approach the ideal performance of the proposed optimal fusion scheme.