Our Optical Networking and Sensing department is leading world-class research into the next generation of optical networks and sensing systems that will power ICT-based social solutions for years. From forward-looking theoretical studies to cutting-edge experiments to world- and industry-first technology field trials, we deliver globally recognized innovation that looks into the future and translates it into present reality. Read our optical networking and sensing news and publications from our team of researchers.
We introduce anchor vectors to monitor Rayleigh-backscattering variability in a fiber-optic computing system that performs nonlinear random projection for image classification. With a ~0.4-s calibration interval, system stability can be maintained with a linear decoder, achieving an average accuracy of 80%-90%.
GNPy advancements enable accurate and efficient modeling of multiband optical networks for digital twin applications. The developed solvers for Kerr nonlinearity and SRS have been validated through simulation and experimentally in C+L transmission, supporting real-world network planning, design, and performance optimization across disaggregated optical infrastructures.
For the first time, we present an end-to-end AI framework for data analysis in distributed fiber optic sensing. The proposed model eliminates the need for optical phase computation and outperforms traditional data processing pipelines, achieving over 96% recognition accuracy on a diverse acoustic dataset.
Distributed fiber-optic sensing combined with machine learning enables continuous monitoring of telecom infrastructure. We employ generative modeling for event classification, supporting semi supervised learning, uncertainty calibration, and noise resilience. Our approach offers a scalable, data-efficient solution for real-world deployment in complex environments.
We experimentally investigated variable spectral loading in an OMS, identifying performance under best and worst transmission conditions. Metrics and data visualization allowed correlation between channel configurations and OSNR variations, enabling the derivation of a simple spectrum allocation rule.
We report the first trial of network tomography over a live network in a multi-domain environment. We visualize end-to-end optical powers along multiple routes across multiple domains solely from a commercial B00G transponder, enabling performance bottleneck localization, power and routing optimization, and lightpath provisioning.
The 2021 emergence of Brood X cicadas was monitored in situ in our testbed using a DAS system connected to an outdoor telecom fiber over a 16-day period. The spectral and energy characteristics of the cicada calling signal has been measured and analyzed.
We report a record long 200.6 km distributed acoustic sensing (DAS) link without inline ampli-fication, 28.6% improvement of sensing range has been achieved by using three segments of enhanced-scattering fibre (ESF) with progressively higher scattering enhancements.
Fiber sensing function was introduced in 2020 as one of the key technology features for the OpenAPN (all photonics network) developed by IOWN GF (Innovative Optical and Wireless NetworkGlobal Forum) in 2020.To our best knowledge, IOWN GF is the first global standard developmentorganization or technology forum that studied fiber sensing technology for telecommunication anddata communication networks, because it brings new feature and benefits to the networkoperators (such as making network operation more efficient, and bringing new values to theexisting network infrastructure), as shown in the examples above.
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.
