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Channel Estimation for Holographic Communications in Hybrid Near-Far Field

Shaohua Yue, Shuhao Zeng, Liang Liu, Boya Di

TL;DR

This work tackles channel estimation for holographic communications in a hybrid near-field/far-field scenario where large antenna apertures push users into the Fresnel region. It introduces a joint angular-polar domain transform to capture both near-field and far-field features and analyzes a power diffusion effect that degrades sparsity in traditional representations. Based on this, the authors develop PD-OMP, a power-diffusion-aware OMP algorithm that does not require prior knowledge of the numbers of near-field and far-field paths, and uses a diffusion-based support set update to improve accuracy. Simulations show PD-OMP outperforms state-of-the-art hybrid-field estimators, achieves substantial NMSE reductions, and demonstrates that the SNR can guide the selected diffusion range, reducing pilot overhead in holographic 6G systems.

Abstract

To realize holographic communications, a potential technology for spectrum efficiency improvement in the future sixth-generation (6G) network, antenna arrays inlaid with numerous antenna elements will be deployed. However, the increase in antenna aperture size makes some users lie in the Fresnel region, leading to the hybrid near-field and far-field communication mode, where the conventional far-field channel estimation methods no longer work well. To tackle the above challenge, this paper considers channel estimation in a hybrid-field multipath environment, where each user and each scatterer can be in either the far-field or the near-field region. First, a joint angular-polar domain channel transform is designed to capture the hybrid-field channel's near-field and far-field features. We then analyze the power diffusion effect in the hybrid-field channel, which indicates that the power corresponding to one near-field (far-field) path component of the multipath channel may spread to far-field (near-field) paths and causes estimation error. We design a novel power-diffusion-based orthogonal matching pursuit channel estimation algorithm (PD-OMP). It can eliminate the prior knowledge requirement of path numbers in the far field and near field, which is a must in other OMP-based channel estimation algorithms. Simulation results show that PD-OMP outperforms current hybrid-field channel estimation methods.

Channel Estimation for Holographic Communications in Hybrid Near-Far Field

TL;DR

This work tackles channel estimation for holographic communications in a hybrid near-field/far-field scenario where large antenna apertures push users into the Fresnel region. It introduces a joint angular-polar domain transform to capture both near-field and far-field features and analyzes a power diffusion effect that degrades sparsity in traditional representations. Based on this, the authors develop PD-OMP, a power-diffusion-aware OMP algorithm that does not require prior knowledge of the numbers of near-field and far-field paths, and uses a diffusion-based support set update to improve accuracy. Simulations show PD-OMP outperforms state-of-the-art hybrid-field estimators, achieves substantial NMSE reductions, and demonstrates that the SNR can guide the selected diffusion range, reducing pilot overhead in holographic 6G systems.

Abstract

To realize holographic communications, a potential technology for spectrum efficiency improvement in the future sixth-generation (6G) network, antenna arrays inlaid with numerous antenna elements will be deployed. However, the increase in antenna aperture size makes some users lie in the Fresnel region, leading to the hybrid near-field and far-field communication mode, where the conventional far-field channel estimation methods no longer work well. To tackle the above challenge, this paper considers channel estimation in a hybrid-field multipath environment, where each user and each scatterer can be in either the far-field or the near-field region. First, a joint angular-polar domain channel transform is designed to capture the hybrid-field channel's near-field and far-field features. We then analyze the power diffusion effect in the hybrid-field channel, which indicates that the power corresponding to one near-field (far-field) path component of the multipath channel may spread to far-field (near-field) paths and causes estimation error. We design a novel power-diffusion-based orthogonal matching pursuit channel estimation algorithm (PD-OMP). It can eliminate the prior knowledge requirement of path numbers in the far field and near field, which is a must in other OMP-based channel estimation algorithms. Simulation results show that PD-OMP outperforms current hybrid-field channel estimation methods.
Paper Structure (15 sections, 17 equations, 5 figures, 1 table, 1 algorithm)

This paper contains 15 sections, 17 equations, 5 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Scenario Description
  4. Hybrid-field Channel model
  5. Model for far-field paths
  6. Model for near-field paths
  7. Overall Hybrid-field Channel Model
  8. Signal Model
  9. Channel Representation in Joint Angular-Polar Domain
  10. Power Diffusion in the Joint Angular-Polar Domain
  11. Power Diffusion-based Compressed Sensing Algorithm Design
  12. Simulation Results
  13. Conclusion
  14. proof of Lemma 1
  15. proof of Proposition 1

Figures (5)

  • Figure 1: The hybrid channel model with a linear holographic antenna array.
  • Figure 2: Power diffusion effect in the joint angular-polar domain.
  • Figure 3: The NMSE performance of different algorithms with the increase of SNR.
  • Figure 4: The NMSE performance of different algorithms with the increase of pilot length.
  • Figure 5: The NMSE performance of PD-OMP of different $\alpha$ with the increase of SNR.

Theorems & Definitions (2)

  • proof
  • proof