Constrained RIS Phase Profile Optimization and Time Sharing for Near-field Localization

TL;DR

This paper explores phase profile design and time sharing strategies for RIS to enhance near-field localization accuracy, deriving theoretical bounds and demonstrating improved performance over conventional methods.

Contribution

It introduces a new localization-optimal phase profile design for RIS with prior user location knowledge and proposes a practical time sharing implementation.

Findings

Proposed phase profile outperforms random and directional codebook designs in PEB.

Derived closed-form Fisher information matrix and position error bounds.

Demonstrated practical implementation of beam weighting through time sharing.

Abstract

The rising concept of reconfigurable intelligent surface (RIS) has promising potential for Beyond 5G localization applications. We herein investigate different phase profile designs at a reflective RIS, which enable non-line-of-sight positioning in nearfield from downlink single antenna transmissions. We first derive the closed-form expressions of the corresponding Fisher information matrix (FIM) and position error bound (PEB). Accordingly, we then propose a new localization-optimal phase profile design, assuming prior knowledge of the user equipment location. Numerical simulations in a canonical scenario show that our proposal outperforms conventional RIS random and directional beam codebook designs in terms of PEB. We also illustrate the four beams allocated at the RIS (i.e., one directional beam, along with its derivatives with respect to space dimensions) and show how their relative weights according to the optimal solution can be practically implemented through time sharing (i.e., considering feasible beams sequentially).