Active and Passive Beamforming Design for Reconfigurable Intelligent Surface Assisted CR-NOMA Networks

In this paper, a underlay cognitive radio inspired nonorthogonal multiple access (CR-NOMA) network assisted by the reconfigurable intelligent surface (RIS) technique is conceived to maximize the energy efficiency (EE), while all the cognitive users (CUs) are located in the “dead zone”. In particular, the CUs could only receive the information from the cognitive base station (CBS) via RIS. The EE maximization optimization problem which is a non-convex problem has been constructed to realize joint beamforming design at both the CBS and RIS with the constraints of the primary user’s (PU) interference power restriction and the CUs’ rate fairness. Moreover, we propose the alternating pragmatic iterative algorithm (APIA) to optimize the nonconvex optimization problem until the final value of EE converges. Based on the simulation results, our proposed algorithm attains the significant gain than the two benchmarks of the random phase scheme as well as the fixed phase scheme on the RIS