| 1. |
- Cao, Yuan, et al.
(author)
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Hybrid Trusted/Untrusted Relay Based Quantum Key Distribution over Optical Backbone Networks
- 2021
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In: IEEE Journal on Selected Areas in Communications. - 0733-8716 .- 1558-0008. ; 39:9, s. 2701-2718
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Journal article (peer-reviewed)abstract
- Quantum key distribution (QKD) has demonstrated a great potential to provide future-proofed security, especially for 5G and beyond communications. As the critical infrastructure for 5G and beyond communications, optical networks can offer a cost-effective solution to QKD deployment utilizing the existing fiber resources. In particular, measurement-device-independent QKD shows its ability to extend the secure distance with the aid of an untrusted relay. Compared to the trusted relay, the untrusted relay has obviously better security, since it does not rely on any assumption on measurement and even allows to be accessed by an eavesdropper. However, it cannot extend QKD to an arbitrary distance like the trusted relay, such that it is expected to be combined with the trusted relay for large-scale QKD deployment. In this work, we study the hybrid trusted/untrusted relay based QKD deployment over optical backbone networks and focus on cost optimization during the deployment phase. A new network architecture of hybrid trusted/untrusted relay based QKD over optical backbone networks is described, where the node structures of the trusted relay and untrusted relay are elaborated. The corresponding network, cost, and security models are formulated. To optimize the deployment cost, an integer linear programming model and a heuristic algorithm are designed. Numerical simulations verify that the cost-optimized design can significantly outperform the benchmark algorithm in terms of deployment cost and security level. Up to 25% cost saving can be achieved by deploying QKD with the hybrid trusted/untrusted relay scheme while keeping much higher security level relative to the conventional point-to-point QKD protocols that are only with the trusted relays.
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| 2. |
- Lin, Rui, 1988, et al.
(author)
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Minimizing Spontaneous Raman Scattering Noise for Quantum Key Distribution in WDM Networks
- 2021
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In: 2021 Optical Fiber Communications Conference and Exhibition, OFC 2021 - Proceedings.
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Conference paper (peer-reviewed)abstract
- We model the SRS impact on QKD when sharing C-band for quantum and classical communications in WDM networks and find the optimal wavelength allocation leading to >26% increase of achievable transmission distance for quantum signals.
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| 3. |
- Lin, Rui, 1988, et al.
(author)
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Modeling and Minimizing Spontaneous Raman Scattering for QKD Secured DWDM Networks
- 2021
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In: IEEE Communications Letters. - 1558-2558 .- 1089-7798. ; 25:12, s. 3918-3921
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Journal article (peer-reviewed)abstract
- Quantum key distribution (QKD) provides information-theoretic security based on quantum mechanics. Integrating QKD with classical data traffic by using wavelength division multiplexing (WDM) techniques in a single fibre is a cost-efficient way to improve security in legacy infrastructure. In such a system, the main noise source to the quantum channel is spontaneous Raman scattering (SRS) caused by the classical channels. In this letter we introduce a channel allocation strategy for both quantum and classical signals to minimize the SRS noise. A use case that quantum and classical channels co-exist in a dense WDM system is investigated. The results show >26% increase of achievable transmission distance for the QKD system when implementing the introduced channel allocation strategy. Moreover, a network updating plan is proposed, which provides a guideline to light the new wavelengths for classical communications while minimizing the SRS noise to quantum channels.
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| 4. |
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| 5. |
- Xue, Lei, 1992, et al.
(author)
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SOA pattern effect mitigation by neural network based pre-equalizer for 50G PON
- 2021
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In: Optics Express. - 1094-4087 .- 1094-4087. ; 29:16, s. 24714-24722
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Journal article (peer-reviewed)abstract
- Semiconductor optical amplifier (SOA) is widely used for power amplification in O-band, particularly for passive optical networks (PONs) which can greatly benefit its advantages of simple structure, low power consumption and integrability with photonics circuits. However, the annoying nonlinear pattern effect degrades system performance when the SOA is needed as a pre-amplifier in PONs. Conventional solutions for pattern effect mitigation are either based on optical filtering or gain clamping. They are not simple or sufficiently flexible for practical deployment. Neural network (NN) has been demonstrated for impairment compensation in optical communications thanks to its powerful nonlinear fitting ability. In this paper, for the first time, NN-based equalizer is proposed to mitigate the SOA pattern effect for 50G PON with intensity modulation and direct detection. The experimental results confirm that the NN-based equalizer can effectively mitigate the SOA nonlinear pattern effect and significantly improve the dynamic range of receiver, achieving 29-dB power budget with the FEC limit at 1e-2. Moreover, the well-trained NN model in the receiver side can be directly placed at the transmitter in the optical line terminal to pre-equalize the signal for transmission so as to simplify digital signal processing in the optical network unit.
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| 6. |
- Zheng, Rui, 1990, et al.
(author)
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Prediction and evaluation of the effect of pre-centrifugation sample management on the measurable untargeted LC-MS plasma metabolome
- 2021
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In: Analytica Chimica Acta. - : Elsevier BV. - 0003-2670 .- 1873-4324. ; 1182
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Journal article (peer-reviewed)abstract
- Optimal handling is the most important means to ensure adequate sample quality. We aimed to investigate whether pre-centrifugation delay time and temperature could be accurately predicted and to what extent variability induced by pre-centrifugation management can be adjusted for. We used untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics to predict and evaluate the influence of pre-centrifugation temperature and delayed time on plasma samples. Pre-centrifugation temperature (4, 25 and 37 °C; classification rate 87%) and time (5–210 min; Q2 = 0.82) were accurately predicted using Random Forest (RF). Metabolites uniquely reflecting temperature and temperature-time interactions were discovered using a combination of RF and generalized linear models. Time-related metabolite profiles suggested a perturbed stability of the metabolome at all temperatures in the investigated time period (5–210 min), and the variation at 4 °C was observed in particular before 90 min. Fourteen and eight metabolites were selected and validated for accurate prediction of pre-centrifugation temperature (classification rate 94%) and delay time (Q2 = 0.90), respectively. In summary, the metabolite profile was rapidly affected by pre-centrifugation delay at all temperatures and thus the pre-centrifugation delay should be as short as possible for metabolomics analysis. The metabolite panels provided accurate predictions of pre-centrifugation delay time and temperature in healthy individuals in a separate validation sample. Such predictions could potentially be useful for assessing legacy samples where relevant metadata is lacking. However, validation in larger populations and different phenotypes, including disease states, is needed.
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