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.

Posts

Bayesian Data Reweighting Improves Multimodal Retrieval for Knowledge-Based Visual Question Answering

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Multimodal retrievers are essential for knowledge-based visual question answering, where they retrieve external evidence for image-question pairs. However, existing contrastive training methods typically treat all unmatched query-document pairs as equally informative negatives, which is problematic because many unmatched documents may still be semantically relevant or partially useful. We propose Bayesian Data Reweighting, a probabilistic framework that models query-document importance as latent variables and adaptively infers posterior weights to downweight likely false negatives. With closed-form posterior updates under conjugate priors and stochastic EM optimization, our method consistently improves retrieval accuracy across three retrievers and seven knowledge-based VQA benchmarks.

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Turning Every Telecom Cable into a City-Wide Sensor Network

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Verizon and NEC Laboratories America turned live telecom fiber into a city-wide sensing network. By repurposing existing optical infrastructure, the system detects vibrations along fiber routes, cutting cable damage incidents and improving response times. The approach also enables AI models that adapt to new, unseen routes without manual labeling.

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Mix-CLAP: Teaching Audio AI to Work in the Noisy Real World

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Mix-CLAP from NEC Laboratories America delivers near-Transformer accuracy for sound event classification at a fraction of the compute cost, using dual lightweight encoders and adaptive, noise-aware inference for real-world edge deployment.

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A Low-cost Wavelength Selectable Distributed Vibration Sensor with a Unified Sensitivity for the Whole Route Security Monitoring in PONs

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We demonstrate a low-cost wavelength selectable distributed vibration sensor to monitor the whole routes in a 1×32 PON architecture with a unified sensitivity. The results obtained from the lab and a field testbed are presented.

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Bridging the Domain Gap in DAS: Adapting Vision Foundation Models for Infrastructure Security

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Distributed Acoustic Sensing may suffer severe cross-day domain shift. We bridge this gap by encoding 1D phasesignals into physics-informed 3-channel gradient tensors andadapting Vision Foundation Models (ViT-B/16), achieving superior threat detection over baselines.

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Field Trial of Urban Monitoring over Telecom Networks with Rayleigh-based DTSS

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We present field trial on urban monitoring over telecom networks using Rayleigh-based distributed temperature/ strain sensor (DTSS), showing the capability of detecting subtle infrastructure signatures including manhole locations, road traffic, sprinklers and underground leakage events.

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Leveraging digital twin technologies: all-photonics networks-as-a-service for Data Center Xchange in the era of AI

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This tutorial paper presents a data center exchange (Data Center Xchange, DCX) architecture for all-photonics networks-as-a-service in distributed data center infrastructures, enabling the creation of a virtual large-scale data center by directly interconnecting geographically distributed data centers in metropolitan areas. In contrast to existing vendor-driven optical networking approaches, the proposed architecture adopts an operator-driven and open digital twin paradigm, leveraging cloud-native transponder architectures and open tools/interfaces such as GNPy and CMIS/TAI, and a user–carrier collaborative control framework. In particular, the cloud-native architecture enables operators to flexibly develop, deploy, and manage their own control and automation functions across transponders and controllers using container-based software components. Key requirements for such an architecture in the era of AI are identified: support for low-latency operations, scalability, reliability, and flexibility within a single network architecture; the ability to add new operator-driven automation functionalities based on an open networking approach; and the ability to control and manage remotely deployed transponders connected via access links with unknown physical parameters. We propose a set of technologies that enable digital twin operations for optical networks, including a cloud-native architecture for coherent transceivers, remote transponder control, fast end-to-end optical path provisioning, transceiver-based physical-parameter estimation incorporating digital longitudinal monitoring, and optical line system calibration, demonstrating their feasibility through field validations.

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Mobile Orbital Domain-based Hierarchical Routing with Joint Path and Gateway Selection

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We propose to jointly optimize path and gateway selection to achieve load balancing for mobile orbital domain-based hierarchical routing in satellite networks. The load at bottleneck gateway satellites can be reduced by 22% on average.

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Multi-Fiber/Multi-DAS Array System with Clock-Free Synchronization

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We demonstrate distributed fiber-optic acoustic sensing that employs a mechanical synchronizer to achieve sample-level synchronization of signals across independent sensors.This enables phase-noise suppression and bandwidth extension in standard multi-fiber optical cables without hardware modification.

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Rapid State-of-Polarization Change-Point Detection via Minimum Lossy Coding Length

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We propose a rapid state-of-polarization disturbance change-point detection and localization method using lossy coding length of kernel features. Field experiments validateaccurate detection of subtle changes and precise localization, enabling reliable fiber identification and monitoring.

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