Compressive Near-Field Wideband Channel Estimation for THz Extremely Large-scale MIMO Systems
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866916871233601536 |
|---|---|
| author | Wang, Jionghui Wang, Hongwei Fang, Jun Li, Lingxiang Chen, Zhi |
| author_facet | Wang, Jionghui Wang, Hongwei Fang, Jun Li, Lingxiang Chen, Zhi |
| contents | We consider the channel acquisition problem for a wideband terahertz (THz) communication system, where an extremely large-scale array is deployed to mitigate severe path attenuation. In channel modeling, we account for both the near-field spherical wavefront and the wideband beam-splitting phenomena, resulting in a wideband near-field channel. We propose a frequency-independent orthogonal dictionary that generalizes the standard discrete Fourier transform (DFT) matrix by introducing an additional parameter to capture the near-field property. This dictionary enables the wideband near-field channel to be efficiently represented with a two-dimensional (2D) block-sparse structure. Leveraging this specific sparse structure, the wideband near-field channel estimation problem can be effectively addressed within a customized compressive sensing framework. Numerical results demonstrate the significant advantages of our proposed 2D block-sparsity-aware method over conventional polar-domain-based approaches for near-field wideband channel estimation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_22727 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Compressive Near-Field Wideband Channel Estimation for THz Extremely Large-scale MIMO Systems Wang, Jionghui Wang, Hongwei Fang, Jun Li, Lingxiang Chen, Zhi Signal Processing We consider the channel acquisition problem for a wideband terahertz (THz) communication system, where an extremely large-scale array is deployed to mitigate severe path attenuation. In channel modeling, we account for both the near-field spherical wavefront and the wideband beam-splitting phenomena, resulting in a wideband near-field channel. We propose a frequency-independent orthogonal dictionary that generalizes the standard discrete Fourier transform (DFT) matrix by introducing an additional parameter to capture the near-field property. This dictionary enables the wideband near-field channel to be efficiently represented with a two-dimensional (2D) block-sparse structure. Leveraging this specific sparse structure, the wideband near-field channel estimation problem can be effectively addressed within a customized compressive sensing framework. Numerical results demonstrate the significant advantages of our proposed 2D block-sparsity-aware method over conventional polar-domain-based approaches for near-field wideband channel estimation. |
| title | Compressive Near-Field Wideband Channel Estimation for THz Extremely Large-scale MIMO Systems |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2507.22727 |