Optimization of multiple-channel cooperative spectrum sensing in Rayleigh fading environment

In this paper, we consider a cognitive radio network (CRN) where different secondary users (SUs) have the different detection signal-to-noise ratios for the same primary user channel in Rayleigh fading environment. We formulate the optimization problem of multi-channel cooperative spectrum sensing (CSS) to maximize the average throughput of the CRN by jointly optimizing the SUs assignment and the sensing time. Considering the optimization problem is non-convex, we transform the optimization problem to two subproblems: the SUs assignment and the sensing time setting. Specifically, a maximum cost function reduction algorithm and water-filling compensation algorithm are proposed to solve the SUs assignment. An iterative algorithm is used to optimize the sensing time. Numerical results show that the proposed algorithms can achieve the performance which is close to that of exhaustive algorithm. Moreover, the joint design can further improve the average throughput of the CRN.