An analytical multiobjective optimization of joint spectrum sensing and power control in cognitive radio networks

The paper deals with the problem of joint spectrum sensing and power control optimization for a multichannel, multiple-user cognitive radio network. In particular, we investigate trade-off factors in designing efficient spectrum sensing techniques to maximize the throughputs and minimize the interferences. To maximize the throughputs of secondary users and minimize the interferences to primary users, it requires for a joint determination of the sensing and transmission parameters of the secondary users, such as sensing times, decision threshold vectors, and power allocation vectors. There is a conflict between these two objectives, thus a multiobjective optimization problem is introduced. We propose an analytical approach based on Newton's methods and nonlinear barrier method to solve this large-scale joint multiobjective optimization problem.