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.

翻译：在地面网络（尤其是城市区域）中，小区边缘用户常因高路径损耗、阴影效应和小区间干扰（ICI）面临显著的容量限制。本文提出将高空平台站（HAPS）集成至地面网络，使地面基站（BS）能够通过HAPS中继发送给小区边缘用户的数据，从而利用视距（LoS）链路缓解上述问题。我们构建了一个能量效率（EE）最大化问题，以联合设计基站与HAPS处的波束成形向量，旨在提升小区边缘用户性能。由于所得问题非凸，我们开发了基于图神经网络（GNN）的在线优化框架，该框架能有效捕捉网络拓扑结构。数值结果表明，所提出的HAPS辅助架构提升了网络性能，特别是增大了第5百分位能量效率，从而改善了小区边缘用户的服务质量。