Sum Rate Maximization for Multi-IRS Assisted Downlink NOMA with Mobile Users

Intelligent reflection surface (IRS) has been recognized as an emerging revolutionary technology for the next generation wireless communication. In this paper, we consider a novel multi-IRS assisted downlink non-orthogonal multiple access (NOMA) network to enhance the system capacity. The superposed signals are transmitted from the base station (BS) to multiple mobile users via multi-IRS reflection. We formulate the sum rate maximization problem by optimizing reflection coefficients. In order to solve the non-convex optimization problem, we utilize the methods of semidefinite relaxation (SDR) and Gaussian randomization. Furthermore, our simulation results prove that the performance of the proposed multi-IRS-NOMA system with optimal reflection coefficients is significantly enhanced.