Phase Shift design in RIS Empowered Networks: From Optimization to AI-based Models

Abstract

Reconfigurable intelligent surfaces (RISs) offer the potential to customize the radio propagation environment for wireless networks. To fully exploit the advantages of RISs in wireless systems, the phases of the reflecting elements must be jointly designed with conventional communication resources, such as beamformers, the transmit power, and computation time. However, due to the unique constraints on the phase shifts and the massive numbers of reflecting units and users in large-scale networks, the resulting optimization problems are challenging to solve. This paper provides a review of the current optimization methods and artificial-intelligence-based methods for handling the constraints imposed by RISs and compares them in terms of the solution quality and computational complexity. Future challenges in phase-shift optimization involving RISs are also described, and potential solutions are discussed.