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

TL;DR

This paper proposes a comprehensive framework for indoor user localization and scatterer mapping in B5G/6G networks using RIS and ray tracing models, enhancing positioning accuracy through beamforming and super-resolution algorithms.

Contribution

It introduces a novel approach combining RIS-enabled beam sweeping, signal extraction, and super-resolution techniques validated with 3D ray tracing models for indoor positioning.

Findings

Effective 3D localization of users and scatterers demonstrated

Improved signal measurement diversity with RIS enhances positioning accuracy

Framework validated with realistic ray tracing models

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.