Near-field Localization with a Reconfigurable Intelligent Surface Acting as Lens

TL;DR

This paper explores using a reconfigurable intelligent surface as a lens for near-field localization, demonstrating that it can achieve decimeter-level accuracy within 3 meters at 28 GHz, with different beamforming strategies depending on prior information.

Contribution

It introduces a novel RIS-based lens approach for localization, analyzes Fisher information, and proposes a two-stage algorithm for improved accuracy.

Findings

Positional beamforming outperforms random beamforming with prior info.

Decimeter-level localization accuracy is achievable within 3 meters at 28 GHz.

RIS lens can be effectively used for near-field localization with limited hardware.

Abstract

Exploiting wavefront curvature enables localization with limited infrastructure and hardware complexity. With the introduction of reconfigurable intelligent surfaces (RISs), new opportunities arise, in particular when the RIS is functioning as a lens receiver. We investigate the localization of a transmitter using a RIS-based lens in close proximity to a single receive antenna element attached to reception radio frequency chain. We perform a Fisher information analysis, evaluate the impact of different lens configurations, and propose a two-stage localization algorithm. Our results indicate that positional beamforming can lead to better performance when a priori location information is available, while random beamforming is preferred when a priori information is lacking. Our simulation results for a moderate size lens operating at 28 GHz showcased that decimeter-level accuracy can be attained within 3 meters to the lens.