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

Hyunwoo Park, Hyeon Seok Rou, Giuseppe Thadeu Freitas de Abreu, Sunwoo Kim

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.

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

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 root-mean-square error with full environment-awareness.
Paper Structure (9 sections, 11 equations, 3 figures, 1 table)

This paper contains 9 sections, 11 equations, 3 figures, 1 table.

Table of Contents

  1. Introduction
  2. UE Tracking System and Problem Formulation
  3. UE Tracking System
  4. Problem Formulation
  5. Environment-aware UE Tracking
  6. Search Space Construction
  7. Environment-aware NF UE Tracking
  8. Simulation Results and Case Studies
  9. Conclusion

Figures (3)

  • Figure 1: Tracking trajectories under three representative conditions. The UE traverses propagation zones ➀ LOS+NLOS, ➁ NLOS, ➂ LOS+NLOS, ➃ LOS, ➄ LOS+NLOS, ➅ NLOS, and ➆ blind zone, in order.
  • Figure 2: Spatial distribution of tracking RMSE over the trackable area.
  • Figure 3: Tracking RMSE versus environment-awareness level $\eta$.