Abstract The integration of unconditional security of quantum key distribution (QKD) with the flexibility of unmanned aerial vehicles (UAVs) presents significant potential for the deployment of comprehensive quantum networks. However, imperfect components of practical QKD systems offer avenues for eavesdropping, while the limited payload capacity and vibrations of UAVs present substantial challenges. This paper introduces an orbital angular momentum (OAM) encoding strategy combined with decoy‐state and the measurement‐device‐independent QKD (MDI‐QKD) protocol to address security issues and reference frame misalignment in UAV‐based QKD systems. Nevertheless, the communication performance of the OAM‐MDI‐QKD system is significantly affected by complex environmental challenges in the airborne channel. To improve the degraded communication performance in airborne platforms, an enhanced grey wolf optimization‐differential evolution (GWO‐DE) algorithm is developed, utilizing chaotic mapping and a nonlinear decay factor to strengthen global search and convergence capabilities, which effectively addresses the search limitations of local search algorithms (LSA) when dealing with high‐dimensional objective functions. Simulation results demonstrate that the GWO‐DE algorithm outperforms other traditional optimization algorithms in terms of optimization precision and transmission distance enhancement, with computational speed meeting system requirements.
Abstract The integration of unconditional security of quantum key distribution (QKD) with the flexibility of unmanned aerial vehicles (UAVs) presents significant potential for the deployment of comprehensive quantum networks. However, imperfect components of practical QKD systems offer avenues for eavesdropping, while the limited payload capacity and vibrations of UAVs present substantial challenges. This paper introduces an orbital angular momentum (OAM) encoding strategy combined with decoy‐state and the measurement‐device‐independent QKD (MDI‐QKD) protocol to address security issues and reference frame misalignment in UAV‐based QKD systems. Nevertheless, the communication performance of the OAM‐MDI‐QKD system is significantly affected by complex environmental challenges in the airborne channel. To improve the degraded communication performance in airborne platforms, an enhanced grey wolf optimization‐differential evolution (GWO‐DE) algorithm is developed, utilizing chaotic mapping and a nonlinear decay factor to strengthen global search and convergence capabilities, which effectively addresses the search limitations of local search algorithms (LSA) when dealing with high‐dimensional objective functions. Simulation results demonstrate that the GWO‐DE algorithm outperforms other traditional optimization algorithms in terms of optimization precision and transmission distance enhancement, with computational speed meeting system requirements.
Abstract Unmanned aerial vehicles (UAVs) emerge as a flexible and cost‐effective solution for mobile quantum communication, showing significant potential. Despite the challenges posed by environmental noise in free‐space channels for efficient entanglement distribution, the noise‐resistant properties of high‐dimensional (HD) quantum states provide a promising solution to these issues. This work establishes a HD orbital angular momentum (OAM) entanglement distribution model on a UAV platform, systematically analyzing the effects of environmental conditions and platform parameters. Based on this model, a HD subspace coding protocol is investigated, with optimized subspace dimension and mode sets to enhance the performance. Furthermore, the use of the source modulation technique can significantly improve the key rate and transmission distance of the system. This work holds important implications for expanding UAV platform coverage, improving adaptability to environmental factors, and advancing the development of heterogeneous quantum networks.
The integration of terrestrial- and satellite-based quantum key distribution (QKD) experiments has markedly advanced global-scale quantum networks, showcasing the growing maturity of quantum technologies. Notably, the use of unmanned aerial vehicles (UAVs) as relay nodes has emerged as a promising method to overcome the inherent limitations of fiber-based and low-Earth orbit (LEO) satellite connections. This paper introduces a protocol for measurement-device-independent QKD (MDI-QKD) using photon orbital angular momentum (OAM) encoding, with UAVs as relay platforms. Leveraging UAV mobility, the protocol establishes a secure and efficient link, mitigating threats from untrusted UAVs. Photon OAM encoding addresses reference frame alignment issues exacerbated by UAV jitter. A comprehensive analysis of atmospheric turbulence, state-dependent diffraction (SDD), weather visibility, and pointing errors on free-space OAM-state transmission systems was conducted. This analysis elucidates the relationship between the key generation rate and propagation distance for the proposed protocol. Results indicate that considering SDD significantly decreases the key rate, halving previous data results. Furthermore, the study identifies a maximum channel loss capacity of 26 dB for the UAV relay platform. This result is pivotal in setting realistic parameters for the deployment of UAV-based quantum communications and lays the foundation for practical implementation strategies in the field.
We present a theoretical framework for quantum key distribution (QKD) using orbital angular momentum (OAM) encoded BB84 on an unmanned aerial vehicle (UAV) platform. A unified channel model captures Kolmogorov turbulence, pointing induced misalignment, and finite aperture clipping, enabling quantitative predictions of inter mode crosstalk and the resulting quantum bit error rate (QBER). Using a weak plus vacuum decoy state formulation, we derive composable finite key lower bounds on the secret key rate that incorporate statistical fluctuations, detector dark counts, efficiency mismatch, and error correction leakage. To stabilize performance under non stationary flight conditions, we introduce a lightweight physics informed learning module that combines physical priors with measured link statistics to classify valid pulses, reject corrupted data, and recommend decoding strategies. We outline a complete evaluation pipeline including UAV system architecture, turbulence driven QBER maps, decoy optimization, finite key scaling, and AI calibration metrics. Simulations indicate that under moderate turbulence and milliradian level pointing jitter, the proposed AI assisted method can improve the secret key rate by 10 percent to 30 percent while preserving composable security.
One-time-pad (OTP) can provide unconditionally secure communications between devices with limited resources, but requires continuous key distribution. Existing quantum key distribution (QKD) protocols produce a continuous secret key stream, but cannot be deployed at the devices that have no quantum channels. In this paper, we first propose a scheme, called synchronized random measurement (SRM) to improve the secret key rate of a QKD protocol. Then, we further propose the novel idea of using unmanned aerial vehicles (UAV) as a physical courier to carrier secret key bits generated through QKD at a gateway to all control devices within coverage area of the gateway. When the UAV does not visit a control device to replenish its consumed secret key bits before the bits are depleted, the device suffers from key deficiency and secure communications are interrupted. We formulate an optimization to minimize the number of UAVs needed to cover all control devices, taking into account the limited battery capacity on-board UAVs and the key deficiency requirement. Through simulations, we have confirmed the key quality and rate improvement of the proposed SRM. We have also evaluated the proposed optimization in finding the minimum number of UAVs to cover different numbers of control devices within a gateway coverage area of different sizes. Increasing the coverage area diameter beyond the UAV flight range may require as many UAVs as the number of control devices for a complete service.
Unmanned aerial vehicles (UAV) based on free-space optical (FSO) systems combine the benefits of both the high data rate of the FSO and the mobility of UAV. However, cumulative effects of laser beam divergence and turbulence-induced fading on the received irradiance in the FSO link might allow an external eavesdropper located near the authorized receiver to break the transmission under certain conditions. Quantum key distribution (QKD) is a technique of secure communication that employs quantum mechanics-based cryptography principles. A combination of a continuous-variable quantum key distribution (CV-QKD) and Gaussian modulation of quantum coherent states (GMCS) enables a relatively secure communication system against collective attacks over FSO transmission links. However, the performance is restricted and degraded due to the influence of atmospheric turbulence and excess noise. This paper aims to evaluate the performance of a secured UAV-based FSO system utilizing prepare and measure CV-QKD protocol based on GMCS under collective attack in terms of quantum bit error rate (QBER), outage probability, and secret key rate (SKR) considering the impairments of the FSO channel, link budget, deviations in the position and attitude angles of the UAV, channel fluctuating transmittance, and excess noise. The system parameters, including transmit power, receiver’s field-of-view, and beam divergence angle, are optimized to satisfy the system’s design criteria of threshold-QBER=10−3and threshold outage probability=10−2. The proposed system tolerates boresight displacement up to 7 cm with the optimized values. The Closed-form expressions and analytical results are confirmed by Monte-Carlo simulations.
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.