Interference Management Strategies for HAPS-Enabled vHetNets in Urban Deployments

TL;DR

This paper explores interference management strategies in HAPS-enabled vHetNets, combining AI and optimization techniques to improve spectral efficiency in urban environments with shared spectrum usage.

Contribution

It introduces novel centralized and distributed interference management approaches tailored for HAPS-enabled vHetNets, highlighting AI's role in reducing complexity.

Findings

Distributed approaches achieve spectral efficiency similar to centralized methods.

Distributed strategies require less global information and lower complexity.

Preliminary results show effective interference mitigation in urban vHetNets.

Abstract

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.