Near-Field User Localization and Channel Estimation for XL-MIMO Systems: Fundamentals, Recent Advances, and Outlooks
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Abstract (arXiv)
Extremely large-scale multiple-input multipleoutput (XL-MIMO) is believed to be a cornerstone of sixth-generation (6G) wireless networks. XL-MIMO uses more antennas to both achieve unprecedented spatial degrees of freedom (DoFs) and exploit new electromagnetic (EM) phenomena occurring in the radiative near-field. The near-field effects provide the XL-MIMO array with depth perception, enabling precise localization and spatially multiplexing jointly in the angle and distance domains. This article delineates the distinctions between near-field and far-field propagation, highlighting the unique EM characteristics introduced by having large antenna arrays. It thoroughly examines the challenges these new near-field characteristics pose for user localization and channel estimation and provides a comprehensive review of new algorithms developed to address them. The article concludes by identifying critical future research directions.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Jul 2024.
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2025Lightweight Deep Learning-Based Channel Estimation for RIS-Aided Extremely Large-Scale MIMO Systems on Resource-Limited Edge Devicescited by 0
- 2026Physical-AI: From Channel Awareness to Environmental Intelligence in 6G Wireless Networkscited by 0
- 2026Reliable Near-Field Multi-User Positioning Informed by Two-Stage MUSICcited by 0
- 2026Reliable Near-Field Multi-User Positioning Informed by Two-Stage MUSIC8 Sep 2026
- 2026Physical-AI: From Channel Awareness to Environmental Intelligence in 6G Wireless Networks12 May 2026
- 2025Lightweight Deep Learning-Based Channel Estimation for RIS-Aided Extremely Large-Scale MIMO Systems on Resource-Limited Edge Devices13 Jul 2025