RIS-assisted near-field localization using practical phase shift model.

Our research focuses on examining the problem of localizing user equipment (UE) in the uplink scenario using reconfigurable intelligent surfaces (RIS) based lens. We carry out a thorough analysis of the Fisher information matrix (FIM) and assess the influence of various RIS-based lens configurations using an actual RIS phase-dependent amplitude variations model. Furthermore, to reduce the complexity of the maximum likelihood (ML) estimator, a simple localization algorithm-based angular expansion is presented.

Configuring reconfigurable intelligent surfaces using a practical codebook approach.

It is proven that the scattering, reflection, and refraction properties of electromagnetic signals can be adapted and managed by using reconfigurable intelligent surfaces (RISs). In this paper, we have investigated the performance of a single-input-single-output (SISO) wideband system in terms of achievable data rate by optimizing the phases of RIS elements and performing a fair power allocation for each subcarrier over the entire bandwidth. A new beamforming codebook is developed from which the maximizing signal-to-noise (SNR) configuration is selected.