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Intelligent Beamforming and Handover via Physics-Informed Beam-Aware CKM Diffusion — arXiv:2609.34704

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.34704
License (as archived): CC0-1.0
Archived: 2026-10-08T01:36:58.653Z
SHA-256 of the archived text: 491be79e2232c32ac1f93c2a6673ba15d0865f5df85f7afcbf603ac7265cb2ca
Stable URL of this page: https://metraipolis.com/documento/dc_e018a78bf752

How to cite

Intelligent Beamforming and Handover via Physics-Informed Beam-Aware CKM Diffusion — arXiv:2609.34704 — arXiv (en), https://arxiv.org/abs/2609.34704 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_e018a78bf752 (Metraipolis archive dc_e018a78bf752, sha256 491be79e2232c32ac1f93c2a6673ba15d0865f5df85f7afcbf603ac7265cb2ca)

BibTeX

@misc{dce018a78bf752,
  title = {Intelligent Beamforming and Handover via Physics-Informed Beam-Aware CKM Diffusion — arXiv:2609.34704},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.34704},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_e018a78bf752; sha256 491be79e2232c32ac1f93c2a6673ba15d0865f5df85f7afcbf603ac7265cb2ca},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.34704. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Downlink communications from base stations (BSs) to unmanned aerial vehicles (UAVs) in sixth-generation (6G) networks require precise beam alignment to overcome severe mobile communication path loss. However, traditional exhaustive beam sweeping relies on discrete codebooks and consumes valuable air-interface resources for online measurements, rendering it inefficient for highly dynamic aerial environments. In this paper, we propose BeamCKMDiff, a physics-informed generative diffusion framework designed to construct high-fidelity continuous beam-aware channel knowledge maps (BeamCKMs). Unlike existing empirical approaches, BeamCKMDiff employs a diffusion transformer (DiT) architecture featuring a dual-path conditioning mechanism. It integrates an analytical line-of-sight (LoS) beam prior with environmental topologies, while simultaneously embedding continuous beamforming vectors through an adaptive layer normalization (adaLN) mechanism. Building upon this differentiable generative mapping, we propose a CKM-based end-to-end continuous beamforming and proactive dual-BS handover algorithm. By analytically propagating gradients through the reverse diffusion process, the proposed framework enables successive convex approximation (SCA)-based beamforming optimization in the computational domain, effectively bypassing physical pilot scanning. Simulation results demonstrate that BeamCKMDiff achieves a normalized mean square error (NMSE) of --23.96 dB, establishing a highly reliable spatial prior. Compared to discrete beam sweeping and LoS-assumed baselines, the proposed CKM-based beamforming adapts to non-LoS (NLoS) conditions, providing accurate beam alignment and higher spectral efficiency. Furthermore, the integrated dual-BS handover mechanism eliminates blockage-induced link outages, ensuring robust connectivity for high-mobility aerial platforms.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-09-29 in eess.SP).
Categorie arXiv: Signal Processing (eess.SP).
Pagina del lavoro: https://arxiv.org/abs/2609.34704 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-08T01:11:02.827Z dalla pagina https://arxiv.org/catchup/eess.SP/2026-09-29?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).