Control and Placement of Finite-Resolution Intelligent Surfaces in IoT Systems with Imperfect CSI

TL;DR

This paper explores how to effectively control and position finite-resolution reconfigurable intelligent surfaces in IoT networks with imperfect channel knowledge, aiming to optimize interference suppression and network performance.

Contribution

It introduces algorithms for RIS control with noisy, local channel info and analyzes placement strategies considering hardware limitations and control degrees.

Findings

Algorithms for RIS control under imperfect CSI

Placement guidelines based on analytical performance metrics

Validation of results through simulations

Abstract

In this paper, we study the advantages of using reconfigurable intelligent surfaces (RISs) for interference suppression in single-input single-output (SISO) distributed Internet of Things (IoT) networks. Implementing RIS-assisted networks confronts various problems, mostly related to the control and placement of the RIS. To tackle the control-related challenges, we consider noisy and local channel knowledge, based on which we devise algorithms to optimize the potentially distributed RISs to achieve an overall network objective, such as the sum-rate. We use a network with a centralized RIS as a benchmark for our comparisons. We further assume low-bit phase shifters at the RIS to capture real-world hardware limitations. We also study the placement of the RIS and analytically quantify the minimum required degrees-of-control for the RIS as a function of its location to guarantee a specific network performance metric and verify the results via simulations.