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arXiv · 2606.00244

GNN-based Online Beamforming Design for HAPS-Assisted NTN

Lavanya S S Anjapuli·Animesh Yadav·Halim Yanikomeroglu
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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.

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Lavanya S S Anjapuli, Animesh Yadav, Halim Yanikomeroglu. 2026-05-29. GNN-based Online Beamforming Design for HAPS-Assisted NTN. https://arxiv.org/abs/2606.00244

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