Phase Shift Compression for Control Signaling Reduction in IRS-Aided Wireless Systems: Global Attention and Lightweight Design

A potential 6G technology known as intelligent reflecting surface (IRS) has recently gained much attention from academia and industry. However, acquiring the optimized quantized phase shift (QPS) presents challenges for the IRS due to the phenomenon of signaling storms. In this paper, we attempt to solve the above problem by proposing two deep learning models, the global attention phase shift compression network (GAPSCN) and the simplified GAPSCN (S-GAPSCN). In GAPSCN, we propose a novel attention mechanism that emphasizes a greater number of meaningful features than traditional attention mechanisms. Additionally, S-GAPSCN is built with an asymmetric architecture to meet the practical constraints on the computation resources of the IRS controller. Moreover, in S-GAPSCN, to compensate for the performance degradation caused by simplifying the model, we design a low-computation complexity joint attention-assisted multi-scale network (JAAMSN) module in the decoder of S-GAPSCN. Simulation results demonstrate that the proposed global attention mechanism achieves prominent performance compared to the existing attention mechanisms and the proposed GAPSCN can achieve reliable reconstruction performance compared to existing state-of-the-art models. Furthermore, the proposed S-GAPSCN can approach the performance of the GAPSCN at a much lower computational cost.

I. Introduction

Intelligent reflecting surfaces (IRS), as promising wireless innovations with the development of microelectromechanical systems (MEMS) and metamaterials, have recently been attracting much attention in wireless communications and the Internet of Things (IoT) [2], [3]. IRSs are two-dimensional, man-made surfaces with low-cost, passive reflecting elements that have adjustable phases and are connected to base stations (BS) or access points (APs) through a smart controller. Specifically, the reflecting elements (e.g., printed dipoles) passively reflect impinging signals without any radio frequency (RF) chains, enabling implementation and management at significantly lower hardware and energy costs compared to traditional active antenna arrays. Additionally, IRSs are characterized by their low profile, lightweight, and conformal geometry, making them easy to mount on or remove from environmental objects for deployment or replacement. Furthermore, IRSs can serve as auxiliary devices in wireless networks and can be easily integrated into them, providing great flexibility and compatibility with existing wireless systems (e.g., cellular or WiFi).