Cooperative sensing with detection threshold optimization in cognitive radio networks

Spectrum sensing is a key enabling technology for cognitive radio networks where secondary users (SUs) are allowed to opportunistically utilize the potentially unused frequency band without causing harmful interference to the licensed users. Cooperative spectrum sensing has been proposed to significantly improve spectrum sensing accuracy by taking advantage of the cooperation among geographically distributed multiple SUs. In this paper, we present a cooperative spectrum sensing model with an individual energy detection threshold for each SU and formulate cooperative spectrum sensing as a nonlinear optimization problem to minimize the probability of false alarm subject to the constraint of missed detection probability. We then propose a suboptimal scheme based on a heuristic algorithm by assigning a distinct detection threshold to each individual cooperative spectrum sensing SU. Numerical results show that given a threshold of missed detection probability, the proposed scheme compared with the existing work can achieve a significant reduction in the false alarm probability, indicating that more spectrum opportunities can be identified by SUs.