Recent Advances in Near-Field Beam Training and Channel Estimation for XL-MIMO Systems

April 08, 2025 ยท The Cartographer ยท ๐Ÿ› arXiv.org

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
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"Title-pattern auto-detect: Recent Advances in Near-Field Beam Training and Channel Estimation for XL-MIMO Systems"

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Authors Ming Zeng, Ji Wang, Xingwang Li, Wanming Hao, Zheng Chu, Wenwu Xie, Xianbin Wang, Quoc-Viet Pham arXiv ID 2504.05578 Category cs.IT: Information Theory Cross-listed eess.SP Citations 0 Venue arXiv.org Last Checked 4 days ago
Abstract
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.
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