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arXiv · 2506.09225

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

Hao Jiang·Zhaolin Wang·Yue Liu·Hyundong Shin·Arumugam Nallanathan·Yuanwei Liu
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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 mobility 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.

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Hao Jiang, Zhaolin Wang, Yue Liu, Hyundong Shin, Arumugam Nallanathan, Yuanwei Liu. 2025-06-10. Near-Field Sensing Enabled Predictive Beamforming: Fundamentals, Framework, and Opportunities. https://arxiv.org/abs/2506.09225

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