Next-generation wireless networks are evolving towards architectures that integrate terrestrial and non-terrestrial networks (NTN), unitedly known as vertical heterogeneous networks (vHetNets). This integration is vital to address the increasing demand for coverage, capacity, and new services in urban environments. Among NTN platforms, high altitude platform stations (HAPS) play a promising role in future vHetNets due to their strategic positioning in the stratosphere. In HAPS-enabled vHetNets, various tiers can operate within the same frequency band, creating a harmonized-spectrum integrated network. Although this harmonization significantly enhances spectral efficiency, it also introduces challenges, with interference being a primary concern. This paper investigates vHetNets comprising HAPS and terrestrial macro base stations (MBSs) operating in a shared spectrum, where interference becomes a critical issue. The unique constraints of HAPS-enabled vHetNets further complicate the interference management problem. To address these challenges, we explore various strategies to manage interference in HAPS-enabled vHetNets. Accordingly, we discuss centralized and distributed approaches that leverage tools based on mathematical optimization and artificial intelligence (AI) to solve interference management problems. Preliminary numerical evaluations indicate that distributed approaches achieve spectral efficiency comparable to the centralized algorithm, while requiring lower complexity and less reliance on global information.

翻译：下一代无线网络正朝着整合地面与非地面网络（NTN）的架构演进，这类统一架构被称为垂直异构网络（vHetNets）。该集成对于满足城市环境中日益增长的覆盖范围、容量和新服务需求至关重要。在各类NTN平台中，高空平台基站（HAPS）凭借其在平流层的战略定位，在未来vHetNets中扮演着重要角色。在HAPS赋能的vHetNets中，不同层级可在相同频段内协同工作，形成频谱一体化的融合网络。尽管这种频谱协同能显著提升频谱效率，但也带来了新的挑战，其中干扰问题尤为突出。本文研究了由HAPS与地面宏基站（MBS）在共享频谱中运行的vHetNets系统，其中干扰成为关键瓶颈。HAPS赋能vHetNets特有的约束条件进一步加剧了干扰管理问题的复杂性。为应对这些挑战，我们深入探讨了多种适用于HAPS赋能vHetNets的干扰管理策略。相应地，我们系统论述了基于数学优化与人工智能（AI）工具的集中式与分布式解决方案。初步数值评估表明，分布式方法在达到与集中式算法相当频谱效率的同时，具有更低的计算复杂度且对全局信息的依赖性更弱。