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GNN-based Online Beamforming Design for HAPS-Assisted NTN
[Submitted on 29 May 2026 (v1), last revised 15 Jul 2026 (this v · 2026-05-30 · via eess.SP updates on arXiv.org

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Abstract:In terrestrial networks, especially in urban areas, cell-edge users often face significant capacity limitations due to high path loss, shadowing, and inter-cell interference (ICI). This paper proposes integrating a high-altitude platform station (HAPS) into terrestrial networks, where terrestrial base stations (BS) can alleviate these issues by relaying data intended for cell-edge users via HAPS, thereby leveraging line-of-sight (LoS) links. We formulate an energy-efficiency (EE) maximization problem to jointly design beamforming vectors at the BS and HAPS with the goal of improving cell-edge user performance. Since the resulting problem is non-convex, we develop an online optimization framework based on a graph neural networks (GNN), which effectively captures the network topology. Numerical results show that the proposed HAPS-assisted architecture improves network performance, particularly by increasing the 5th-percentile EE, thereby enhancing service for cell-edge users.

Submission history

From: Animesh Yadav [view email]
[v1] Fri, 29 May 2026 18:22:43 UTC (986 KB)
[v2] Wed, 15 Jul 2026 04:27:31 UTC (985 KB)