Environment-aware Near-field UE Tracking under Partial Blockage and Reflection

TL;DR

This paper introduces an environment-aware near-field user tracking method for large aperture arrays that leverages surface geometry and LOS/NLOS indicators to improve accuracy, especially under partial blockages and reflections.

Contribution

It presents a novel near-field tracking approach that incorporates environment awareness and surface geometries, outperforming traditional far-field methods in complex scenarios.

Findings

Achieves 0.22 m RMS error with full environment-awareness.

Outperforms far-field baselines in accuracy.

Improves tracking robustness under partial blockages.

Abstract

This paper proposes an environment-aware near-field (NF) user equipment (UE) tracking method for extremely large aperture arrays. By integrating known surface geometries and tracking the line-of-sight (LOS) and non-line-of-sight (NLOS) indicators per antenna element, the method captures partial blockages and reflections specific to the NF spherical-wavefront regime, which are unavailable under the conventional far-field (FF) assumption. The UE positions are tracked by maximizing the cosine similarity between the predicted and received channels, enabling tracking even under complete LOS obstruction. Simulation results confirm that increasing environment-awareness improves accuracy, and that NF consistently outperforms FF baselines, achieving a $0.22\,\mathrm{m}$ root-mean-square error with full environment-awareness.