Air-to-Ground Communications Beyond 5G: CoMP Handoff Management in UAV Network

TL;DR

This paper introduces a novel CoMP transmission strategy for UAV-based air-to-ground networks, improving coverage and handoff reliability by using Poisson-Delaunay triangulation for efficient UAV cooperation.

Contribution

It proposes a computationally efficient CoMP method based on Poisson-Delaunay triangulation, reducing overhead and enhancing coverage in UAV networks with seamless handoff management.

Findings

Outperforms Voronoi-based schemes in coverage probability with handoffs.

Reduces system resource costs through fixed UAV serving sets.

Enhances network coverage and load balancing.

Abstract

Air-to-ground (A2G) networks, using unmanned aerial vehicles (UAVs) as base stations to serve terrestrial user equipments (UEs), are promising for extending the spatial coverage capability in future communication systems. Coordinated transmission among multiple UAVs significantly improves network coverage and throughput compared to a single UAV transmission. However, implementing coordinated multi-point (CoMP) transmission for UAV mobility requires complex cooperation procedures, regardless of the handoff mechanism involved. This paper designs a novel CoMP transmission strategy that enables terrestrial UEs to achieve reliable and seamless connections with mobile UAVs. Specifically, a computationally efficient CoMP transmission method based on the theory of Poisson-Delaunay triangulation is developed, where an efficient subdivision search strategy for a CoMP UAV set is designed to minimize search overhead by a divide-and-conquer approach. For concrete performance evaluation, the cooperative handoff probability of the typical UE is analyzed, and the coverage probability with handoffs is derived. Simulation results demonstrate that the proposed scheme outperforms the conventional Voronoi scheme with the nearest serving UAV regarding coverage probabilities with handoffs. Moreover, each UE has a fixed and unique serving UAV set to avoid real-time dynamic UAV searching and achieve effective load balancing, significantly reducing system resource costs and enhancing network coverage performance.