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arXiv:2601.11117

UAV-Deployed OAM-BB84 QKD: Turbulence- and Misalignment-Resilient Decoy-State Finite-Key Security with AI-Assisted Calibration

Linxier Deng

quant-phSubmitted Jan 16, 2026• Announced Jan 19, 2026• 0 citations
arXivHTMLPDF

Abstract

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.

Comments
7 pages, 7 figures

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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.
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.
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This paper develops a comprehensive analytical framework for modeling and performance evaluation of unmanned aerial vehicles (UAVs)-to-ground quantum communication links, incorporating key physical impairments such as beam divergence, pointing errors at both transmitter and receiver, atmospheric attenuation, turbulence-induced fading, narrow field-of-view (FoV) filtering, and background photon noise. To overcome the limitations of conventional wide-beam assumptions, we introduce a grid-based approximation for photon capture probability that remains accurate under tightly focused beams. Analytical expressions are derived for the quantum key generation rate and quantum bit error rate (QBER), enabling fast and reliable system-level evaluation. Our results reveal that secure quantum key distribution (QKD) over UAV-based free-space optical (FSO) links requires beam waists below 10 cm and sub-milliradian tracking precision to achieve Mbps-level key rates and QBER below 10−310^{-3}10−3. Additionally, we highlight the critical role of receiver FoV in balancing background noise rejection and misalignment tolerance, and propose adaptive FoV tuning strategies under varying illumination and alignment conditions. The proposed framework provides a tractable and accurate tool for the design, optimization, and deployment of next-generation airborne quantum communication systems.
Unmanned aerial vehicles (UAVs)-based free-space optics (FSO)/quantum key distribution (QKD) systems require high-precision pointing mechanisms. This increases system complexity and limits rapid deployment for lightweight and energy-constrained UAVs. This paper proposes a modulating retroreflector (MRR)-equipped UAV architecture for BB84-QKD systems that enables simplified yet accurate tracking while relaxing pointing requirements. A realistic quantum channel model is developed, for which we newly derive the channel probability distribution of transmittance (PDT). Capitalizing on the derived channel PDT, several QKD performance metrics are analytically obtained. Numerical results verify the feasibility of the proposed MRR-aided UAV for practical QKD deployment, highlight its effectiveness over conventional UAV-ground systems, and validate the accuracy of the developed analytical framework.
This letter investigates a continuous-variable quantum key distribution (CV-QKD) protocol based on Gaussian-modulated coherent states over unmanned aerial vehicle (UAV)-based free-space optical (FSO) links. A realistic fading channel model is developed, including atmospheric turbulence, extinction, and UAV-induced pointing errors. We perform distance-dependent modulation variance optimization to maximize the secret key rate (SKR) under three scenarios: asymptotic, finite-block size (FBS), and FBS with adaptive optics (AO), based on numerical simulations incorporating a realistic UAV-FSO channel model. The results show that finite-size effects reduce the secure transmission range to ~800 m, while AO extends it to ~930 m. Furthermore, optimal modulation improves key rates by up to 40% compared to fixed modulation. This is the first work to jointly model UAV-FSO channel fluctuations, optimize modulation, and quantify finite-size security with AO, confirming the feasibility of CV-QKD for UAV-based communications.
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=10−3=10^{-3}=10−3and threshold outage probability=10−2=10^{-2}=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.