Optical Networking and SensingRead our Optical Networking and Sensing publications from our team of researchers. We are leading world-class research into the next generation of optical networks and sensing systems that will power ICT-based social solutions for years. We advance globally acknowledged innovation by engaging in visionary theoretical research, pioneering experiments, and leading technology field trials. Our work not only foresees the future but also transforms it into today’s reality.

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Feasibility study on scour monitoring for subsea cables of offshore wind turbines using distributed fiber optic sensors

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Subsea cables are critical components of offshore wind turbines and are subjected to scour. Monitoring the scour conditions of subsea cables plays significant roles in improving safety and operation efficiency and reducing the levelized cost of electricity. This paper presents a feasibility study on monitoring subsea cables using distributed fiber optic sensors (DFOS), aiming to evaluate the technical and economic performance of utilizing DFOS to detect, locate, and quantify scour conditions. Laboratory experiments were conducted to test the response ofDFOS measurements to the change of support conditions which were used to simulate scour effects, and a finite element model was developed to investigate the impact of scour on the mechanical responses of subsea cables in different scour scenarios. Economic analysis of three methods, involving the use of DFOS, discrete sensors, and underwater robots, is performed via a case study. The results showed that the proposed method has technical and economic benefits for monitoring subsea cables. This research offers insights into monitoring subsea structuresfor offshore wind turbines.

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Integration of Fiber Optic Sensing and Sparse Grid Sensors for Accurate Fault Localization in Distribution Systems

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Fault localization in power distribution networks is essential for rapid recovery and enhancing system resilience. While Phasor Measurement Units (PMUs or ?PMUs) providehigh-resolution measurements for precise fault localization, their widespread deployment is cost-prohibitive. Distributed Fiber Optic Sensing (DFOS) offers a promising alternative for event detection along power lines using collocated optical fiber; however, it cannot independently differentiate between events and pinpoint exact fault locations. This paper introduces an innovative framework that combines DFOS with sparsely deployed PMUs for accurate fault localization. The proposed approach first utilizes a Graph Attention Network (GAT) model to capture spatial and temporal correlations from synchronized PMU and DFOS measurements, effectively identifying fault zones. High-spatial- resolution DFOS measurements further refine the fault locationwithin the identified zone. Singular Value Decomposition (SVD) is applied to extract feature vectors from DFOS measurements, enhancing the convergence speed of the GAT model. Thisintegrated solution significantly improves localization accuracy while minimizing reliance on extensive deployment of PMUs.

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Accelerating Distributed Machine Learning with AllReduce Reconfiguration Based on Optical Circuit Switching

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We propose to apply optical circuit switching to enable dynamic AllReduce reconfiguration for accelerating distributed machine learning. With simulated annealing-based optimization, theproposed AllReduce reconfiguration approach achieves 31% less average training time than existing solutions.

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First City-Scale Deployment of DASs with Satellite Imagery and AI for Live Telecom Infrastructure Management

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We demonstrate real-time fiber risk assessment and dynamic network routing in live metro networks using deployed DASs, satellite imagery, and large-scale AI, achieving the first significantreduction in fiber failures in four years

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High Definition-Distributed Fiber Optic Sensing and Smart Intersection application

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Distributed fiber optics sensing is applied for traffic management in the intersection. The high-definition fiber sensing data streaming is applied as source and YOLO computer vision model isemployed for event detection classification and localization.

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QoT-Driven Control and Optimization in Fiber-Optic WDM Network Systems

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This paper outlines QoT-driven optimization strategies in coherent fiber-optic WDM networks, addressing distinct transmission scenarios, QoT metrics, control-plane methodologies, and emerging trends to enhance network reliability, flexibility and capacity.

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Robust Phase Noise Power Spectral Density Estimation Using Multi-Laser Interferometry

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We jointly estimate the phase noise power spectral densities of multiple lasers using interferometry between different combinations of laser pairs. We demonstrate a beat-frequency trackingmethod that allows under-sampling of interferometric products without phase jumps.

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Span-based Polarization Sensing in Cables Without Reflectors

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Polarization-based, multi-span sensing over a link without reflection-back circuits is demonstrated experimentally. It is shown that distributed reflection from Rayleigh scattering can serveas an alternative to reflectors after spatial averaging of received state-of-polarization

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Toward Intelligent and Efficient Optical Networks: Performance Modeling, Co-existence, and Field Trials

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Optical transmission networks require intelligent traffic adaptation and efficient spectrum usage. We present scalable machine learning (ML) methods for network performance modeling, andfield trials of distributed fiber sensing and classic optical network traffic coexistence.

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Phase-noise Tolerant Per-span Phase and Polarization Sensing

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Subsea cables include a supervisory system that monitors the health of the amplifier pumps and fiber loss on per span basis. In some of the cables, the monitoring is achieved optically and passively using high-loss loop back paths and wavelength selective reflectors. By sending monitoring pulses through the supervisory channel and comparing the phases and polarizations of the returning pulses reflected by consecutive reflectors, dynamic disturbances affecting individual spans can be monitored on a per span basis. Such per-span phase monitoring techniques require high phase coherence compared to DAS systems since the spans are 10s of kms long compared to typical DAS resolution of meters. A time-frequency spread technique was demonstrated to limit the coherence length requirement, however the limits of its effectiveness was not quantified. In this paper we present a detailed analysis of the trade-off between implementation complexity and the phase noise tolerance for given span length by lab experiments.

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