Phase Shift Optimization Algorithm for Achievable Rate Maximization in Reconfigurable Intelligent Surface-Assisted THz Communications

Terahertz (THz) band communications are considered a crucial technology to support future applications, such as ultra-high bit rate wireless local area networks, in the next generation of communication systems. In this work, we consider an ultra-massive multiple-input multiple-output (UM-MIMO) THz system operating typical indoor scenario where direct link between transmitter and receiver is obstructed due surrounding obstacles. To help establish communication, assume aid nearby reconfigurable intelligent surface (RIS) whose phase shifts can be adjusted. configure individual RIS elements, formulate problem constrained achievable maximization. Due large dimensions optimization problem, apply accelerated proximal gradient (APG) method, which results low complexity algorithm that copes with non-convex shift constraint through simple element-wise normalization. Our numerical demonstrate effectiveness proposed even when considering realistic discrete shifts’ quantization imperfect channel knowledge. Furthermore, comparison against existing alternatives reveals improvements 30% 120% terms range, for reference 100 Gbps using approach only 81 elements.