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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.18752 |
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| _version_ | 1866909802197680128 |
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| author | Yang, Dehui Xi, Feng Zhu, Yanxian |
| author_facet | Yang, Dehui Xi, Feng Zhu, Yanxian |
| contents | Channel estimation is a critical task in extremely large-scale multiple-input multiple-output (XL-MIMO) systems for 6G wireless communications. A hybrid-field channel model effectively characterizes the mixed far-field and near-field scattering components in practical XL-MIMO systems. In this paper, we propose a convex demixing approach for hybrid-field channel estimation within the atomic norm minimization (ANM) framework. By promoting sparsity of the far-field and near-field components directly in the continuous parameter domain, a demixing scheme that minimizes a weighted sum of two atomic norms is proposed. We show that the resulting ANM is equivalent to a computationally feasible semi-definite programming (SDP). Numerical experiments on simulated data demonstrate that our method outperforms existing approaches for hybrid-field channel estimation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_18752 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Convex Demixing Approach for Hybrid-Field Channel Estimation of XL-MIMO Systems via Atomic Norm Minimization Yang, Dehui Xi, Feng Zhu, Yanxian Information Theory Channel estimation is a critical task in extremely large-scale multiple-input multiple-output (XL-MIMO) systems for 6G wireless communications. A hybrid-field channel model effectively characterizes the mixed far-field and near-field scattering components in practical XL-MIMO systems. In this paper, we propose a convex demixing approach for hybrid-field channel estimation within the atomic norm minimization (ANM) framework. By promoting sparsity of the far-field and near-field components directly in the continuous parameter domain, a demixing scheme that minimizes a weighted sum of two atomic norms is proposed. We show that the resulting ANM is equivalent to a computationally feasible semi-definite programming (SDP). Numerical experiments on simulated data demonstrate that our method outperforms existing approaches for hybrid-field channel estimation. |
| title | A Convex Demixing Approach for Hybrid-Field Channel Estimation of XL-MIMO Systems via Atomic Norm Minimization |
| topic | Information Theory |
| url | https://arxiv.org/abs/2509.18752 |