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.
@article{arxiv.2506.09225,
title = {Near-Field Sensing Enabled Predictive Beamforming: Fundamentals, Framework, and Opportunities},
author = {Hao Jiang and Zhaolin Wang and Yue Liu and Hyundong Shin and Arumugam Nallanathan and Yuanwei Liu},
journal= {arXiv preprint arXiv:2506.09225},
year = {2025}
}