Stable Matching-Based Two-Phase Resource Allocation Framework for Multi-UAV-Assisted Covert Communications

Unmanned aerial vehicles (UAVs) assisted covert communication networks, a significant component of the secure Internet of Things (IoT), comprise highly maneuverable aerial relays, massive ground-based sensor nodes (GNs), legitimate receivers and a warden that integrate signal-sensing and detection capabilities. However, existing works mainly focus on energy-efficient relaying or trajectory optimization for UAV-assisted sensor networks, neglecting the joint impact of limited battery capacity of GNs and the stringent requirement for UAVs to avoid detection by the warden, which will lead to severe energy waste and a low covert rate. To tackle this issue, we propose a stable matching-based two-phase resource allocation framework for multi-UAV-assisted covert communications (STRMC) under symmetric information. Specifically, we introduce the minimum weight stable matching (MWSM) algorithm to derive the energy-optimal and covert-rate-optimal pairings in each phase, leveraging the structural properties of all stable matchings and graph-theoretic techniques. Simulation results show that the proposed STRMC significantly improves both covert throughput and energy efficiency compared with existing works.