Joint Beamforming and Artificial Noise Optimization for Secure Transmissions in MISO-NOMA Cognitive Radio System with SWIPT

Abstract

The integration of non-orthogonal multiple access (NOMA) in cognitive radio (CR) networks has demonstrated how to enhance spectrum efficiency and achieve massive connectivity for future mobile networks. However, security is still a challenging issue due to the wireless transmission environment and the broadcast nature of NOMA. Thus, in this paper, we investigate a beamforming design with artificial noise (AN) to improve the security of a multi-user downlink, multiple-input single-output (MISO) NOMA-CR network with simultaneous wireless information and power transfer (SWIPT). To further support power-limited, battery-driven devices, energy-harvesting (EH) users are involved in the proposed network. Specifically, we investigate the optimal AN, power-splitting ratios, and transmission beamforming vectors for secondary users and EH users in order to minimize the transmission power of the secondary network, subject to the following constraints: a minimum signal-to-interference-plus-noise ratio at the secondary users, minimum harvested energy by secondary users and EH users, maximum power at the secondary transmitter, and maximum permissible interference with licensed users. The proposed solution for the challenging non-convex optimization problem is based on the semidefinite relaxation method. Numerical results show that the proposed scheme outperforms the conventional scheme without AN, the zero-forcing-based scheme and the space-division multiple-access-based method.