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In this paper, we propose a state-of-the-art downlink communicationtransceiver design for transmissive reconfigurable metasurface (RMS)-enabledsimultaneous wireless information and power transfer (SWIPT) networks.Specifically, a feed antenna is deployed in the transmissive RMS-basedtransceiver, which can be used to implement beamforming. According to therelationship between wavelength and propagation distance, the spatialpropagation models of plane and spherical waves are built. Then, in the case ofimperfect channel state information (CSI), we formulate a robust systemsum-rate maximization problem that jointly optimizes RMS transmissivecoefficient, transmit power allocation, and power splitting ratio design whiletaking account of the non-linear energy harvesting model and outage probabilitycriterion. Since the coupling of optimization variables, the whole optimizationproblem is non-convex and cannot be solved directly. Therefore, the alternatingoptimization (AO) framework is implemented to decompose the non-convex originalproblem. In detail, the whole problem is divided into three sub-problems tosolve. For the non-convexity of the objective function, successive convexapproximation (SCA) is used to transform it, and penalty function method anddifference-of-convex (DC) programming are applied to deal with the non-convexconstraints. Finally, we alternately solve the three sub-problems until theentire optimization problem converges. Numerical results show that our proposedalgorithm has convergence and better performance than other benchmarkalgorithms.

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