Energy‐Efficient and Resource‐Optimized Clustering for Unmanned Aerial Vehicle Quantum Networks
TL;DR
Simulation results demonstrate that ENW‐ACA significantly outperforms traditional non‐clustering routing across multiple performance metrics, including energy efficiency, quantum resource utilization, and network throughput, while maintaining its advantages as the network scale expands.
Abstract
Quantum communication represents a cutting‐edge research frontier, yet its wide‐area deployment remains constrained by infrastructure limitations. Unmanned aerial vehicle (UAV) technology, with its inherent flexibility and rapid deployability, offers a promising solution for dynamic quantum network expansion, giving rise to the emerging paradigm of UAV quantum networks. However, these networks face critical challenges, including energy and quantum resource constraints, as well as fragile quantum links. To address these issues, we propose an efficient clustering‐based communication scheme and develop an Energy‐Neighbor Weight Adaptive Clustering Algorithm (ENW‐ACA). This algorithm incorporates a multi‐index cluster head election strategy and a multi‐level routing mechanism to achieve low energy dissipation, high quantum resource utilization, and improved network throughput. Simulation results demonstrate that ENW‐ACA significantly outperforms traditional non‐clustering routing across multiple performance metrics, including energy efficiency, quantum resource utilization, and network throughput, while maintaining its advantages as the network scale expands. These findings provide theoretical support for clustering and routing design in UAV quantum networks and establish a technical foundation for their large‐scale deployment.