Near-Field Wideband Channel Estimation for Extremely Large-Scale RIS-Aided Communication Systems

TL;DR

This paper introduces a novel wideband channel estimation method for extremely large RIS-assisted systems, effectively handling near-field and far-field hybrid channels in mmWave/THz frequencies using a frequency-independent dictionary and compressed sensing.

Contribution

It proposes a new frequency-independent orthogonal dictionary and a compressed sensing framework to efficiently estimate wideband cascaded channels with hybrid near-field and far-field characteristics.

Findings

Significantly improves estimation accuracy over conventional methods.

Effectively models hybrid near-field and far-field channels.

Demonstrates robustness in wideband mmWave/THz scenarios.

Abstract

This paper studies wideband channel estimation for OFDM systems assisted by extremely large RIS (XL-RIS). Due to the large aperture of XL-RISs, the user equipment may operate in the near-field region, while the base station-XL-RIS link remains in the far field, leading to a cascaded channel with hybrid near-field and far-field characteristics. Moreover, wideband effects further complicate channel estimation in mmWave/THz systems. To address these challenges, we propose a frequency-independent orthogonal dictionary by augmenting the discrete Fourier transform (DFT) matrix with additional parameters, which enables an efficient representation of the wideband cascaded channel using a two-dimensional block-sparse structure. Based on this property, the considered channel estimation problem is effectively solved within a tailored compressed sensing framework. Simulation results demonstrate that the proposed method significantly outperforms conventional polar-domain channel estimation approaches in terms of estimation accuracy.