Air-to-Ground Communications for Internet of Things: UAV-based Coverage Hole Detection and Recovery

2026-01-08

IEEE Internet of Things Journal

AI Summary

This work proposes a dynamic coverage restoration framework leveraging drone swarms to address the high cost, reliance on outdated data, and limited real-time recovery capability in detecting and repairing coverage blind spots in terrestrial Internet-of-Things (IoT) networks. The framework integrates Delaunay triangulation with stochastic geometry to establish a scalable aerial base station deployment architecture. It further incorporates a multi-agent cooperative collision-avoidance mechanism and a joint satellite–terrestrial base station scheduling strategy to enable efficient, safe, and on-demand connectivity restoration. Simulation results demonstrate that the proposed approach significantly improves the efficiency of blind spot detection and recovery while substantially reducing both time and operational costs.

Technology Category

• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Uncrewed aerial vehicles (UAVs) play a pivotal role in ensuring seamless connectivity for Internet of Things (IoT) devices, particularly in scenarios where conventional terrestrial networks are constrained or temporarily unavailable. However, traditional coverage-hole detection approaches, such as minimizing drive tests, are costly, time-consuming, and reliant on outdated radio-environment data, making them unsuitable for real-time applications. To address these limitations, this paper proposes a UAV-assisted framework for real-time detection and recovery of coverage holes in IoT networks. In the proposed scheme, a patrol UAV is first dispatched to identify coverage holes in regions where the operational status of terrestrial base stations (BSs) is uncertain. Once a coverage hole is detected, one or more UAVs acting as aerial BSs are deployed by a satellite or nearby operational BSs to restore connectivity. The UAV swarm is organized based on Delaunay triangulation, enabling scalable deployment and tractable analytical characterization using stochastic geometry. Moreover, a collision-avoidance mechanism grounded in multi-agent system theory ensures safe and coordinated motion among multiple UAVs. Simulation results demonstrate that the proposed framework achieves high efficiency in both coverage-hole detection and on-demand connectivity restoration while significantly reducing operational cost and time.

Problem

• coverage hole
• Internet of Things
• UAV
• air-to-ground communications
• connectivity restoration

Innovation

• UAV-assisted coverage
• coverage hole detection
• Delaunay triangulation
• multi-agent collision avoidance
• stochastic geometry