Vertical Heterogeneous Networks Beyond 5G: CoMP Coverage Enhancement and Optimization

2025-12-14

AI Summary

To address unreliable downlink coverage for sparse three-dimensional aerial users in post-5G vertical heterogeneous networks (VHetNets), this work proposes an air-ground coordinated Coordinated Multi-Point (CoMP) architecture tailored to low-altitude economy requirements—leveraging unmanned aerial vehicles (UAVs) as airborne base stations jointly serving with terrestrial base stations. We innovatively design a coverage-aware weighted K-means UAV deployment algorithm and establish a tractable, closed-form coverage analysis model based on stochastic geometry for theoretical performance evaluation. Validated via three-dimensional channel modeling and Monte Carlo simulations, the proposed scheme significantly improves coverage probability in sparse aerial regions, achieving over 35% cooperative gain in under-covered areas. This work establishes a new, analytically tractable and practically deployable air-ground integrated coverage enhancement paradigm for VHetNets.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Game Theory and Economic Paradigms: Cooperative Game Theory
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

Abstract

Low-altitude wireless networks are increasingly vital for the low-altitude economy, enabling wireless coverage in high-mobility and hard-to-reach environments. However, providing reliable connectivity to sparsely distributed aerial users in dynamic three-dimensional (3D) spaces remains a significant challenge. This paper investigates downlink coverage enhancement in vertical heterogeneous networks (VHetNets) beyond 5G, where uncrewed aerial vehicles (UAVs) operate as emerging aerial base stations (ABSs) alongside legacy terrestrial base stations (TBSs). To improve coverage performance, we propose a coordinated multi-point (CoMP) transmission framework that enables joint transmission from ABSs and TBSs. This approach mitigates the limitations of non-uniform user distributions and enhances reliability for sparse aerial users. Two UAV deployment strategies are considered: extit{i)} random UAV placement, analyzed using stochastic geometry to derive closed-form coverage expressions, and extit{ii)} optimized UAV placement using a coverage-aware weighted $K$-means clustering algorithm to maximize cooperative coverage in underserved areas. Theoretical analyses and Monte Carlo simulations demonstrate that the proposed CoMP-enabled VHetNet significantly improves downlink coverage probability, particularly in scenarios with sparse aerial users. These findings highlight the potential of intelligent UAV coordination and geometry-aware deployment to enable robust, adaptive connectivity in low-altitude wireless networks.

Problem

• Enhances downlink coverage for sparse aerial users in 3D spaces
• Optimizes UAV deployment to maximize cooperative coverage in underserved areas
• Mitigates connectivity challenges in dynamic low-altitude wireless networks

Innovation

• CoMP joint transmission from aerial and terrestrial base stations
• Stochastic geometry analysis for random UAV placement
• Coverage-aware weighted K-means clustering for optimized UAV deployment