Robust Beamforming Design in a NOMA Cognitive Radio Network Relying on SWIPT

Abstract

This paper studies a multiple-input-single-output non-orthogonal multiple access cognitive radio network relying on simultaneous wireless information and power transfer. A realistic non- linear energy harvesting model is applied and a power splitting architecture is adopted at each secondary user. Since it is difficult to obtain the perfect channel state information (CSI) in practice, a bounded CSI error model is considered. Our robust beamforming and power splitting ratio are jointly designed for minimizing the transmission power of the cognitive base station. The original non-convex optimization problem is then converted into convex forms by using semi- definite relaxation. For the minimum transmission power problem, we prove that the optimal solution has a limited rank of less than or equal to 2. Our simulation results show that the proposed scheme significantly outperforms its traditional orthogonal multiple access counterpart.