Joint Beamforming, Power, and Channel Allocation in Multiuser and Multichannel Underlay MISO Cognitive Radio Networks

In this paper, we consider joint beamforming, power, and channel allocation in a multiuser and multichannel underlay multiple-input-single-output (MISO) cognitive radio network (CRN). In this system, the primary users' spectrum can be reused by secondary-user transmitters (SU-TXs) to maximize spectrum utilization, whereas intrauser interference is minimized by implementing beamforming at each SU-TX. After formulating the joint optimization problem as a nonconvex mixed-integer nonlinear programming problem, we propose a solution that consists of two stages. In the first stage, a feasible solution for power allocation and beamforming vectors is derived under a given channel allocation by converting the original problem into a convex form with an introduced optimal auxiliary variable and a semidefinite relaxation approach. In the second stage, two explicit searching algorithms, i. e., genetic algorithm (GA) and simulated annealing (SA)-based algorithm, are proposed to determine suboptimal channel allocations. Simulation results show that the beamforming and power and channel allocation with SA algorithm can achieve a close-to-optimal sum rate while having lower computational complexity compared with the beamforming and power and channel allocation with the GA algorithm. Furthermore, our proposed allocation scheme has significant improvement in achievable sum rate compared with the existing zero-forcing beamforming.