Joint Analog and Passive Beamforming Design for IRS-Aided Secure Cognitive NOMA Systems

Abstract

Due to the ability of channel reconfiguration, intelligent reflecting surface (IRS) can be used to boost the secrecy rate of cognitive non-orthogonal multiple access (NOMA) systems. However, the cost and hardware complexity of full-digital beamforming in existing related studies is high, especially for the systems with massive antennas. In this paper, we investigate the secure transmission for IRS-aided cognitive NOMA systems with cost-effective analog beamforming. The secrecy rate of primary user is maximized subject to the quality of service constraint of secondary user via joint analog and passive beamforming optimization. Owing to the non-convexity, we first transform the problem into two subproblems. Then, each subproblem is tackled via the penalty-based algorithm and the successive convex approximation. Simulation results demonstrate that the proposed transmission scheme has higher energy efficiency and can boost the security of IRS-aided cognitive NOMA systems.