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Lecture notes in networks and systems

Quantum Adaptive Graph: A Self-Healing Framework for Unmanned Aerial Vehicle (UAV) Swarms

Sourav Banerjee, Anupam Bhattacharya

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.1007/978-981-96-9494-5_23

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In order to enhance the secrecy transmission of unmanned aerial vehicle (UAV) swarm, a novel physical-layer key generation (PLKG) efficient UAV swarm trajectory planning method is proposed in this work. Different from the existing UAV trajectory planning methods that only focus on collision avoidance, energy saving and improving transmission quality, the proposed method incorporates the PLKG capability into the UAV trajectory design. Based on the findings of the fact that the wireless scattering experienced by UAV signals from different UAV trajectories are typically distinct, the channel randomness oriented PLKG behaves differently for various UAV trajectories. As a result, we propose to incorporate the PLKG metric into the UAV trajectory planning objectives, in order to improve the secrecy of UAV swarm transmissions. The theoretical derivation between UAV swarm PLKG metric and the wireless scattering entropy is obtained, and we propose a channel entropy knowledge sharing mechanism for UAV swarm to achieve PLKG efficient swarm trajectory planning. Simulation results show that the key generation performance can be largely improved in comparison to the traditional secrecy rate maximization oriented UAV swarm trajectory planning.
This study presents "Quantum Lattice," an innovative theoretical framework designed to ensure the security of Unmanned Aerial Vehicle (UAV) swarm communications in the era after quantum computing. Given the risk posed by quantum computing to conventional cryptography techniques, it is imperative to develop security solutions that are immune to quantum attacks specifically designed for UAV systems. Utilizing sophisticated lattice-based encryption, we employ the Short Integer Solution (SIS) problem and a novel Aerial Lattice Traversal (ALT) algorithm to provide strong security while preserving real-time performance essential for UAV operations. Simulations performed on a testbed which incorporates quantum technology show substantial enhancements compared to conventional approaches. These benefits include a 42% decrease in latency, a 28% increase in throughput, a 63% reduction in packet loss, and a 37% decrease in energy consumption, especially in dense swarm setups with up to 1000 nodes. The mathematical principles that underlie our approach, including δ--ary lattices and their cryptographic applications, are thoroughly discussed. In addition, the study investigates the incorporation of our framework with developing technologies like neuromorphic computing and AI-powered adaptive security mechanisms. In the quantum computing era, our results provide a foundation for secure, scalable, and robust UAV swarm operations, effectively tackling significant issues in both civilian and military contexts.