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

Lanqing Zhi, Hongwei Wang, Lingxiang Li, Zhi Chen

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.

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

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.
Paper Structure (11 sections, 33 equations, 4 figures)

This paper contains 11 sections, 33 equations, 4 figures.

Table of Contents

  1. Introduction
  2. System Model and Signal Model
  3. System Model and Notations
  4. Wideband Channel Model
  5. Problem Formulation
  6. Proposed Method
  7. Block Sparsity for a Specific Sub-Carrier Channel
  8. 2D Block-sparse Structure
  9. 2D Block-Sparsity-Aware Wideband Near-field Channel Estimation
  10. Numerical Simulation
  11. Conclusions

Figures (4)

  • Figure 1: Block sparsity in $\boldsymbol{x}_p$.
  • Figure 2: The sparsity of the wideband channel $\boldsymbol{H}$
  • Figure 3: NMSE versus pilot length $T$ when SNR = 10 dB.
  • Figure 4: NMSE versus SNR when T = 700.