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Near-Field Sensing Enabled Predictive Beamforming: Fundamentals, Framework, and Opportunities

  • Hao Jiang
  • , Zhaolin Wang
  • , Yue Liu
  • , Hyundong Shin
  • , Arumugam Nallanathan
  • , Yuanwei Liu

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

The article proposes a novel near-field predictive beamforming framework for high-mobility wireless networks. Specifically, due to the spherical waves and non-uniform Doppler frequencies brought by the near-field region, the new ability of full-dimensional location and velocity sensing is characterized. Building on this foundation, the near-field predictive beamforming framework is proposed to proactively design beamformers for mobile users following arbitrary trajectories. Compared to the conventional far-field counterpart, the near-field predictive beamforming stands out due to: i) Prior- Knowledge-Free Prediction, and ii) Low-Complexity and Generalizable System Design. To realize these advantages, the implementation methods are discussed, followed by a case study confirming the benefits of the proposed framework. Finally, the article highlights promising research opportunities inspired by the proposed framework.

Original languageEnglish
JournalIEEE Communications Magazine
DOIs
Publication statusAccepted/In press - 2026

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