Recent Advances in Near-Field Beam Training and Channel Estimation for XL-MIMO Systems
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917353041690624 |
|---|---|
| author | Zeng, Ming Wang, Ji Hao, Wanming Chu, Zheng Xie, Wenwu Pham, Quoc-Viet |
| author_facet | Zeng, Ming Wang, Ji Hao, Wanming Chu, Zheng Xie, Wenwu Pham, Quoc-Viet |
| contents | Extremely large-scale multiple-input multiple-output (XL-MIMO) is a key technology for next-generation wireless communication systems. By deploying significantly more antennas than conventional massive MIMO systems, XL-MIMO promises substantial improvements in spectral efficiency. However, due to the drastically increased array size, the conventional planar wave channel model is no longer accurate, necessitating a transition to a near-field spherical wave model. This shift challenges traditional beam training and channel estimation methods, which were designed for planar wave propagation. In this article, we present a comprehensive review of state-of-the-art beam training and channel estimation techniques for XL-MIMO systems. We analyze the fundamental principles, key methodologies, and recent advancements in this area, highlighting their respective strengths and limitations in addressing the challenges posed by the near-field propagation environment. Furthermore, we explore open research challenges that remain unresolved to provide valuable insights for researchers and engineers working toward the development of next-generation XL-MIMO communication systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_05578 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Recent Advances in Near-Field Beam Training and Channel Estimation for XL-MIMO Systems Zeng, Ming Wang, Ji Hao, Wanming Chu, Zheng Xie, Wenwu Pham, Quoc-Viet Information Theory Signal Processing Extremely large-scale multiple-input multiple-output (XL-MIMO) is a key technology for next-generation wireless communication systems. By deploying significantly more antennas than conventional massive MIMO systems, XL-MIMO promises substantial improvements in spectral efficiency. However, due to the drastically increased array size, the conventional planar wave channel model is no longer accurate, necessitating a transition to a near-field spherical wave model. This shift challenges traditional beam training and channel estimation methods, which were designed for planar wave propagation. In this article, we present a comprehensive review of state-of-the-art beam training and channel estimation techniques for XL-MIMO systems. We analyze the fundamental principles, key methodologies, and recent advancements in this area, highlighting their respective strengths and limitations in addressing the challenges posed by the near-field propagation environment. Furthermore, we explore open research challenges that remain unresolved to provide valuable insights for researchers and engineers working toward the development of next-generation XL-MIMO communication systems. |
| title | Recent Advances in Near-Field Beam Training and Channel Estimation for XL-MIMO Systems |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2504.05578 |