Sum Rate Optimization in Interference Channel of Cognitive Radio Network

In multiuser cognitive radio (CR) network, we address the problem of joint transmit beamforming (BF) and power control (PC) for secondary users (SUs) when they are allowed to transmit simultaneously with primary users (PUs). The objective is to optimize the network sum rate under the interference constraints of PUs, which is nonconvex problem. Iterative dual subgradient (IDuSuG) algorithm is proposed to solve such problems. It iteratively performs BF and PC to optimize the sum rate, among which minimum mean square error (MMSE) or virtual power-weighed projection (VIP$^2$) is used to design beamformers and subgradient method optimizes the PC. VIP$^2$ algorithm is devised for the case of the interference caused by MMSE beamformer over the threshold. Channel uncertainty is considered and robust algorithm is provided by modifying updates in iterative process. Finally the network sum rates for different PU and SU numbers are assessed for both certainty and uncertainty channel model by simulation.