Multiobjective Joint Design of Finite-Resolution RISs and Downlink Beamforming for Double-RIS-Assisted IoT Networks

This paper investigates the downlink of an internet-of-things (IoT) network with a base station serving multiple IoT devices (IoTDs) with the assistance of two far-apart reconfigurable intelligent surfaces (RISs). We propose joint design of the BS’s beamformer and RISs’ quantized programmable reflecting elements (PREs). Considering the IoTDs’ minimum rate (MR) as the primary optimization objective, we further aim to optimize the multi-objective function of both the MR and sum rate (SR) in the Pareto-optimal sense. We develop convex-solver and closed-form algorithms. Simulations demonstrate that the latter, with scalable complexity, performs as well as the former, which exhibits polynomially increasing complexity. Furthermore, the simulations reveal the advantages of the double-RIS assisted solution over its single-RIS assisted counterpart of the same size.