RIS phase optimization for Near-Field 5G Positioning: CRLB Minimization

This article addresses near-field localization using Reconfigurable Intelligent Surfaces (RIS) in 5G systems, where Line-of-Sight (LOS) between the base station and the user is obstructed. We propose a RIS phase optimization method based on the minimization of the Cramér-Rao Lower Bound (CRLB) for position estimation. The main contributions of the article are: (1) the derivation of the CRLB to optimize the RIS configuration; and (2) the application of the mentioned framework in nearfield considering reflective RIS. The proposed method is validated with simulations, showing an accuracy improvement of RIS phase optimization with respect to the state-of-the-art methods.