Near-field 5D Pose Estimation using Reconfigurable Intelligent Surfaces

Fuente: arXiv
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Autori principali: Sadhu, Srikar Sharma, Mankar, Praful D., Nannuru, Santosh
Natura: Preprint
Pubblicazione: 2025
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author Sadhu, Srikar Sharma
Mankar, Praful D.
Nannuru, Santosh
author_facet Sadhu, Srikar Sharma
Mankar, Praful D.
Nannuru, Santosh
contents The advent of 6G is expected to enable many use cases which may rely on accurate knowledge of the location and orientation of user equipment (UE). The conventional localization methods suffer from limitations such as synchronization and high power consumption required for multiple active anchors. This can be mitigated by utilizing a large dimensional passive reconfigurable intelligent surface (RIS). This paper presents a novel low-complexity approach for the estimation of 5D pose (i.e. 3D location and 2D orientation) of a UE in near-field RIS-assisted multiple-input multiple-output (MIMO) systems. The proposed approach exploits the symmetric arrangement of uniform planar array of RIS and uniform linear array of UE to decouple the 5D problem into five 1D sub-problems. Further, we solve these sub-problems using a total least squares ESPRIT inspired approach to obtain closed-form solutions.
format Preprint
id arxiv_https___arxiv_org_abs_2505_01829
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Near-field 5D Pose Estimation using Reconfigurable Intelligent Surfaces
Sadhu, Srikar Sharma
Mankar, Praful D.
Nannuru, Santosh
Signal Processing
The advent of 6G is expected to enable many use cases which may rely on accurate knowledge of the location and orientation of user equipment (UE). The conventional localization methods suffer from limitations such as synchronization and high power consumption required for multiple active anchors. This can be mitigated by utilizing a large dimensional passive reconfigurable intelligent surface (RIS). This paper presents a novel low-complexity approach for the estimation of 5D pose (i.e. 3D location and 2D orientation) of a UE in near-field RIS-assisted multiple-input multiple-output (MIMO) systems. The proposed approach exploits the symmetric arrangement of uniform planar array of RIS and uniform linear array of UE to decouple the 5D problem into five 1D sub-problems. Further, we solve these sub-problems using a total least squares ESPRIT inspired approach to obtain closed-form solutions.
title Near-field 5D Pose Estimation using Reconfigurable Intelligent Surfaces
topic Signal Processing
url https://arxiv.org/abs/2505.01829