Near-Field Sensing Enabled Predictive Beamforming: Fundamentals, Framework, and Opportunities
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911000008065024 |
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| author | Jiang, Hao Wang, Zhaolin Liu, Yue Shin, Hyundong Nallanathan, Arumugam Liu, Yuanwei |
| author_facet | Jiang, Hao Wang, Zhaolin Liu, Yue Shin, Hyundong Nallanathan, Arumugam Liu, Yuanwei |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_09225 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Near-Field Sensing Enabled Predictive Beamforming: Fundamentals, Framework, and Opportunities Jiang, Hao Wang, Zhaolin Liu, Yue Shin, Hyundong Nallanathan, Arumugam Liu, Yuanwei Signal Processing 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. |
| title | Near-Field Sensing Enabled Predictive Beamforming: Fundamentals, Framework, and Opportunities |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2506.09225 |