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

TL;DR

This paper explores enhancing downlink coverage in 3D low-altitude wireless networks by deploying UAVs as aerial base stations and employing CoMP transmission, with strategies for optimal UAV placement and coverage analysis.

Contribution

It introduces a CoMP framework for UAV and terrestrial base station cooperation and proposes a coverage-aware UAV deployment algorithm for improved connectivity.

Findings

CoMP significantly improves coverage probability in sparse aerial user scenarios.

Stochastic geometry provides closed-form expressions for coverage analysis.

Optimized UAV placement enhances cooperative coverage in underserved areas.

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: \textit{i)} random UAV placement, analyzed using stochastic geometry to derive closed-form coverage expressions, and \textit{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.