RIS-Enabled Localization Continuity Under Near-Field Conditions

TL;DR

This paper explores how reconfigurable intelligent surfaces (RISs) can improve user localization accuracy in near-field conditions, especially when line-of-sight paths are blocked, by exploiting wavefront curvature.

Contribution

It extends prior RIS localization work by analyzing near-field effects and demonstrating potential accuracy improvements through Fisher information analysis.

Findings

Near-field conditions enhance localization accuracy at short distances with LoS.

RIS can still enable localization when LoS is blocked by relying on single reflections.

Wavefront curvature exploitation improves localization performance in near-field scenarios.

Abstract

Reconfigurable intelligent surfaces (RISs) have the potential to enable user localization in scenarios where traditional approaches fail. Building on prior work in single-antenna RIS-enabled localization, we investigate the potential to exploit wavefront curvature in geometric near-field conditions. Via a Fisher information analysis, we demonstrate that while near-field improves localization accuracy mostly at short distances when the line-of-sight (LoS) path is present, it could still provide reasonable performance when this path is blocked by relying on a single RIS reflection.