Optimization of Quantized Phase Shifts for Reconfigurable Smart Surfaces Assisted Communications

TL;DR

This paper addresses the challenge of optimizing quantized phase shifts in reconfigurable smart surfaces to enhance wireless communication performance, proposing a greedy algorithm to improve data rates under practical constraints.

Contribution

It introduces a sub-optimal greedy algorithm for quantized phase-shift configuration in RSS-assisted OFDM systems, considering practical limitations like discrete control and channel errors.

Findings

Proposed algorithm outperforms baseline methods in simulations.

Quantization resolution significantly impacts system performance.

RSS placement affects data rate optimization.

Abstract

Reconfigurable Smart Surface (RSS) is assumed to be a key enabler for future wireless communication systems due to its ability to control the wireless propagation environment and, thus, enhance communications quality. Although optimal and continuous phase-shift configuration can be analytically obtained, practical RSS systems are prone to both channel estimation errors, discrete control, and curse of dimensionality. This leads to relaying on a finite number of phase-shift configurations that is expected to degrade the system's performances. In this paper, we tackle the problem of quantized RSS phase-shift configuration, aiming to maximize the data rate of an orthogonal frequency division multiplexing (OFDM) point-to-point RSS-assisted communication. Due to the complexity of optimally solving the formulated problem, we propose here a sub-optimal greedy algorithm to solve it. Simulation results illustrate the performance superiority of the proposed algorithm compared to baseline approaches. Finally, the impact of several parameters ,e.g., quantization resolution and RSS placement, is investigated.