Evaluation of RIS-Enabled B5G/6G Indoor Positioning and Mapping using Ray Tracing Models

TL;DR

This paper presents a comprehensive framework aimed at user localization and scatterer position estimation in an indoor environment with multipath effects that leverages beam sweeping through codebook-based beamforming at an 1-bit RIS to scan the environment, applies signal component extraction mechanisms, and utilizes a super-resolution algorithm for angle-based positioning of both connected users and scatterers.

Abstract

A Reconfigurable Intelligent Surface (RIS) can significantly enhance network positioning and mapping, acting as an additional anchor point in the reference system and improving signal strength and measurement diversity through the generation of favorable scattering conditions and virtual line-of-sight paths. In this paper, we present a comprehensive framework aimed at user localization and scatterer position estimation in an indoor environment with multipath effects. Our approach leverages beam sweeping through codebook-based beamforming at an 1-bit RIS to scan the environment, applies signal component extraction mechanisms, and utilizes a super-resolution algorithm for angle-based positioning of both connected users and scatterers. To validate the system's effectiveness, accurate 3D ray tracing models are employed, ensuring the robustness and effectiveness of the proposed approach in practical scenarios.

Figures (3)

• Figure 1: The considered RT-based simulation setup where the red point denotes Tx positions, blue point the Rx, and the red and blue point the RIS node.
• Figure 2: Test Rx positions of the UEs.
• Figure 3: Scatterer positions for mapping.