Robust Sum-Rate Maximization in Transmissive RMS Transceiver-Enabled SWIPT Networks

In this article, we propose a state-of-the-art downlink communication transceiver design for transmissive reconfigurable metasurface (RMS)-enabled simultaneous wireless information and power transfer (SWIPT) networks. Specifically, feed antenna is deployed in the RMS-based transceiver, which can be used to implement beamforming. According relationship between wavelength propagation distance, spatial models of plane spherical waves are built. Then, case imperfect channel state (CSI), formulate robust system sum-rate maximization problem that jointly optimizes RMS coefficient, transmit allocation, splitting ratio while taking account nonlinear energy harvesting model outage probability criterion. Since coupling optimization variables, whole nonconvex cannot solved directly. Therefore, alternating (AO) framework implemented decompose original problem. detail, divided into three subproblems solve. For nonconvexity objective function, successive convex approximation (SCA) transform it, penalty function method difference-of-convex (DC) programming applied deal with constraints. Finally, alternately solve until entire converges. Numerical results show our proposed algorithm has convergence better performance than other benchmark algorithms.