Simultaneous Localization and Mapping Using Active mmWave Sensing in 5G NR

TL;DR

This paper introduces an active mmWave sensing approach in 5G NR systems for high-precision SLAM, generating detailed radio maps and accurate user localization through point cloud processing and optimization techniques.

Contribution

It presents a novel active sensing method using 5G NR for SLAM, enabling detailed environmental mapping and precise localization beyond passive sensing limitations.

Findings

Effective point cloud generation from 5G NR signals

Accurate terminal localization through registration and optimization

Validated system performance via simulations and experiments

Abstract

Millimeter-wave (mmWave) 5G New Radio (NR) communication systems, with their high-resolution antenna arrays and extensive bandwidth, offer a transformative opportunity for high-throughput data transmission and advanced environmental sensing. Although passive sensing-based SLAM techniques can estimate user locations and environmental reflections simultaneously, their effectiveness is often constrained by assumptions of specular reflections and oversimplified map representations. To overcome these limitations, this work employs a mmWave 5G NR system for active sensing, enabling it to function similarly to a laser scanner for point cloud generation. Specifically, point clouds are extracted from the power delay profile estimated from each beam direction using a binary search approach. To ensure accuracy, hardware delays are calibrated with multiple predefined target points. Pose variations of the terminal are then estimated from point cloud data gathered along continuous trajectory viewpoints using point cloud registration algorithms. Loop closure detection and pose graph optimization are subsequently applied to refine the sensing results, achieving precise terminal localization and detailed radio map reconstruction. The system is implemented and validated through both simulations and experiments, confirming the effectiveness of the proposed approach.