Near-Field Localization via Reconfigurable Antennas

TL;DR

This paper introduces a novel hybrid precoder design for reconfigurable antennas that significantly enhances near-field user localization accuracy by optimizing EM and baseband precoders, addressing a gap in existing research focused on far-field scenarios.

Contribution

It proposes a joint optimization model for EM and baseband precoders in reconfigurable antennas specifically for near-field localization, which is a novel application.

Findings

Hybrid precoder design reduces user position error bound.

Simulation results show improved localization accuracy over traditional arrays.

The approach effectively leverages EM domain control for near-field scenarios.

Abstract

Reconfigurable antennas (RAs) utilize the electromagnetic (EM) domain to provide dynamic control over antenna radiation patterns, which offers an effective way to enhance power efficiency in wireless links. Unlike conventional arrays with fixed element patterns, RAs enable on-demand beam-pattern synthesis by directly controlling each antenna's EM characteristics. While existing research on RAs has primarily focused on improving spectral efficiency, this paper explores their application for downlink localization. Moreover, the majority of existing works focus on far-field scenarios with little attention on near-field (NF). Motivated by these gaps, we consider a synthesis model in which each antenna generates desired beampatterns from a finite set of EM basis functions. We then formulate a joint optimization problem for the baseband (BB) and EM precoders with the objective of minimizing the user equipment (UE) position error bound (PEB) in NF conditions. Our analytical derivations and extensive simulation results demonstrate that the proposed hybrid precoder design for RAs significantly improves UE positioning accuracy compared to traditional non-reconfigurable arrays.