Reconfigurable Intelligent Surfaces in Dynamic Rich Scattering Environments: BiLSTM-Based Optimization for Accurate User Localization

TL;DR

This paper proposes a biLSTM-based method to optimize reconfigurable intelligent surfaces for improved user localization accuracy in complex, dynamic rich scattering environments, addressing a key challenge in 6G wireless networks.

Contribution

It introduces a novel biLSTM-based approach trained with physics-based simulations to adapt RIS configurations for accurate localization in dynamic rich scattering scenarios.

Findings

Significant improvement in localization accuracy demonstrated in simulations.

Effective adaptation of RIS configurations to changing environments.

BiLSTM approach outperforms traditional static methods.

Abstract

The integration of reconfigurable intelligent surfaces (RIS) in wireless environments offers channel programmability and dynamic control over propagation channels, which is expected to play a crucial role in sixth generation (6G) networks. The majority of RIS-related research has focused on simpler, quasi-free-space conditions, where wireless channels are typically modeled analytically. However, many practical localization scenarios unfold in environments characterized by rich scattering that also change over time. These dynamic and complex conditions pose significant challenges in determining the optimal RIS configuration to maximize localization accuracy. In this paper, we present our approach to overcoming this challenge. This paper introduces a novel approach that leverages a bidirectional long-short term memory (biLSTM) network, trained with a simulator that accurately reflects wave physics, to capture the relationship between wireless channels and the RIS configuration under dynamic, rich-scattering conditions. We use this approach to optimize RIS configurations for enhanced user equipment (UE) localization, measured by mean squared error (MSE). Through extensive simulations, we demonstrate that our approach adapts RIS configurations to significantly improve localization accuracy in such dynamically changing rich scattering environments.