Publications

Utility Pole Localization by Learning From Ambient Traces on Distributed Acoustic Sensing

June 4, 2023/in Publications/by NEC Labs America

Publication Date: 6/4/2023

Event: 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Reference: pp. 1-5, 2023

Authors: Zhuocheng Jiang, NEC Laboratories America, Inc.; Yue Tian, NEC Laboratories America, Inc.; Yangmin Ding, NEC Laboratories America, Inc.; Sarper Ozharar, NEC Laboratories America, Inc.; Ting Wang, NEC Laboratories America, Inc.

Abstract: Utility pole detection and localization is the most fundamental application in aerial-optic cables using distributed acoustic sensing (DAS). The existing pole localization method recognizes the hammer knock signal on DAS traces by learning from knocking vibration patterns. However, it requires many efforts for data collection such as knocking every pole and manually labeling the poles’ locations, making this labor-intensive solution expensive, inefficient, and highly error prone. In this paper, we propose a pole localization solution by learning the ambient data collected from a DAS system, which are vibration patterns excited by random ambient events, such as wind and nearby traffic. In detail, we investigate a universal framework for learning representations of ambient data in the frequency domain by contrastive learning of the similarity of low and high-frequency series. A Gaussian-based data reweighting kernel is employed for eliminating the effect of the label noise. Experimental results demonstrate the proposed methods outperform the existing contrastive learning methods on the real-world DAS ambient dataset.

Publication Link: https://ieeexplore.ieee.org/document/10095252

Real-Time Blind Source Separation with Integrated Photonics for Wireless Signals

May 7, 2023/in Publications/by NEC Labs America

Publication Date: 5/7/2023

Event: CLEO 2023

Reference: SW3O.6: 1-2, 2023

Authors: Thomas Ferreira de Lima, NEC Laboratories America, Inc.; Joshua C. Lederman, Princeton University; Weipeng Zhang, Princeton University; Junqiang Hu, NEC Laboratories America, Inc.; Eric C. Blow, Princeton University; Koji Asahi, NEC Corporation; Yoshiaki Aono, NEC Corporation; Ting Wang, NEC Laboratories America, Inc.; Paul R. Prucnal, Princeton University

Abstract: We demonstrate, for the first time, real-time blind source separation of interfering GHz transmitters using photonic weights controlled by an RF-System-on-Chip FPGA. This analog system achieves multi-antenna signal separation with millisecond execution latency.

Explore Benefits of Distributed Fiber Optic Sensing for Optical Network Service Providers

April 1, 2023/in Publications/by NEC Labs America

Publication Date: 4/1/2023

Event: Journal of Lightwave Technology

Reference: pp.1-9, 2023

Authors: Glenn A. Wellbrock, Verizon; Tiejun J. Xia, Verizon; MIng-Fang Huang, NEC Laboratories America, Inc.; Shaobo Han, NEC Laboratories America, Inc.; Yuheng Chen, NEC Laboratories America, Inc.; Ting Wang, NEC Laboratories America, Inc.; Yoshiaki Aono, NEC Corporation

Abstract: We review various applications of distributed fiber optic sensing (DFOS) and machine learning (ML) technologies that particularly benefit telecom operators’ fiber networks and businesses. By leveraging relative phase shift of the reflectance of coherent Rayleigh, Brillouin and Raman scattering of light wave, the ambient environmental vibration, acoustic effects, temperature and fiber/cable strain can be detected. Fiber optic sensing technology allows optical fiber to support sensing features in addition to its conventional role to transmit data in telecommunications. DFOS has recently helped telecom operators by adding multiple sensing features and proved feasibility of co-existence of sensing and communication systems on same fiber. We review the architecture of DFOS technique and show examples where optical fiber sensing helps enhance network operation efficiency and create new services for customers on deployed fiber infrastructures, such as determination of cable locations, cable cut prevention, perimeter intrusion detection and networked sensing applications. In addition, edge AI platform allows data processing to be conducted on-the-fly with low latency. Based on discriminative spatial-temporal signatures of different events of interest, real-time processing of the sensing data from the DFOS system provides results of the detection, classification and localization immediately.

Publication Link: https://ieeexplore.ieee.org/document/10091246

Data-driven Modelling of EDFAs by Neural Networks

March 13, 2023/in Publications/by NEC Labs America

Publication Date: 3/13/2023

Event: SubOptic 2023

Reference: pp. 1-6, 2023

Authors: Fatih Yaman, NEC Laboratories America, Inc.; Hussam G. Batshon, NEC Laboratories America, Inc.; Daisuke Katsukura, NEC Corporation; Shinsuke Fujisawa, NEC Corporation; Eduardo Mateo, NEC Corporation; Takanori Inoue, NEC Corporation; Yoshihisa Inada, NEC Corporation

Abstract: Dependence of EDFA gain shape on input power and input spectrum shape is modelled using a simple neural network-based architecture for amplifiers with different gains and output powers. The model can predict the gain within ±0.1 dB. Even though the model has good success predicting the performance of the particular EDFA it is trained with, it is not as successful when used to predict a different EDFA, or even the same EDFA with a different pump power. However, retraining the model with a small amount of supplementary data from a second EDFA makes the model able to predict the performance of the second EDFA with little loss in performance.

Improvement of resilience of submarine networks based on fiber sensing

March 13, 2023/in Publications/by NEC Labs America

Publication Date: 3/13/2023

Event: SubOptic 2023

Reference: pp. 1-7, 2023

Authors: Fatih Yaman, NEC Laboratories America, Inc.; Yang Li, NEC Laboratories America, Inc., Georgia State University; Shaobo Han, NEC Laboratories America, Inc.; Eduardo Mateo, NEC Corporation; Takanori Inoue, NEC Corporation; Yoshihisa Inada, NEC Corporation

Abstract: Simultaneous phase and polarization sensing with span length resolution using the supervisory path is demonstrated. It is shown that by measuring polarization rotation matrix of the return paths, instead of monitoring only the state of polarization, location of the polarization disturbance can be determined even for large polarization rotations. By using the polarization rotation matrices, the phase and polarization disturbances are successfully decoupled. How the existing supervisory system and sensing can coexist in new SDM cables that utilizes pump sharing is discussed.

Field Trial of Coexistence and Simultaneous Switching of Real-time Fiber Sensing and 400GbE Supporting DCI and 5G Mobile Services

March 5, 2023/in Publications/by NEC Labs America

Publication Date: 3/5/2023

Event: OFC 2023

Reference: W3H.4: 1-3, 2023

Authors: Yue-Kai Huang, NEC Laboratories America, Inc.; Zehao Wang, Duke University; Ezra Ip, NEC Laboratories America, Inc.; Zhenzhou Qi, Duke University; Gil Zussman, Columbia University; Dan Kilper, Trinity College Dublin; Koji Asahi, NEC Corporation; Hideo Kageshima, NEC Corporation; Yoshiaki Aono, NEC Corporation; Tingjun Chen, Duke University

Abstract: Coexistence of real-time constant-amplitude distributed acoustic sensing (DAS) and 400GbE signals is verified by field trial over metro fibers, demonstrating no QoT impact during co-propagation and supporting preemptive DAS-informed optical path switching before link failure

Publication Link: https://ieeexplore.ieee.org/document/10117373

Polarization Sensing Using Polarization Rotation Matrix Eigenvalue Method

March 5, 2023/in Publications/by NEC Labs America

Publication Date: 3/5/2023

Event: OFC 2023

Reference: W1J.7: 1-3, 2023

Authors: Fatih Yaman, NEC Laboratories America, Inc.; Yang Li, NEC Laboratories America, Inc., Georgia State University; Shaobo Han, NEC Laboratories America, Inc.; Takanori Inoue, NEC Corporation; Eduardo Mateo, NEC Corporation; Yoshihisa Inada, NEC Corporation

Abstract: Polarization-based, multi-span sensing over a link with reflection-back circuits is demonstrated experimentally. By measuring rotation matrices instead of just monitoring polarization, a 35 dB extinction in localization is achieved regardless of the disturbance magnitude.

Publication Link: https://ieeexplore.ieee.org/document/10117264

DAS over 1,007-km Hybrid Link with 10-Tb/s DP-16QAM Co-propagation using Frequency- Diverse Chirped Pulses

February 15, 2023/in Publications/by NEC Labs America

Publication Date: 2/15/2023

Event: Journal of Lightwave Technology

Reference: 41(4): 1077-1086, 2023

Authors: Ezra Ip, NEC Laboratories America, Inc.; Yue-Kai Huang, NEC Laboratories America, Inc.; Ming-Fang Huang, NEC Laboratories America, Inc.; Fatih Yaman, NEC Laboratories America, Inc.; Glenn Wellbrock, Verizon; Tiejun Xia, Verizon; Ting Wang, NEC Laboratories America, Inc.; Koji Asahi, NEC Corporation; Yoshiaki Aono, NEC Corporation

Abstract: We report the first distributed acoustic sensing (DAS) experiment with over >1,000 km reach on a hybrid link comprising of a mixture of field and lab fibers with bi-directional inline Raman amplification after each span. We used 20× frequency-diversity chirped-pulses for the probe signal,and recovered the Rayleigh backscatter using a coherent receiver with correlation detection and diversity combining. A measurand resolution of ∼100 pϵ/√ Hz at a gauge length of 20 meters achieved in the offline experiment. We also demonstrate the first real-time FPGA implementation of chirped-pulse DAS without frequency diversity over a range of 210 km.

Publication Link: https://ieeexplore.ieee.org/document/9937060

Drone Detection and Localization using Enhanced Fiber-Optic Acoustic Sensor and Distributed Acoustic Sensing Technology

February 1, 2023/in Publications/by NEC Labs America

Publication Date: 2/1/2023

Event: Journal of Lightwave Technology

Reference: 41(3): 822-831, 2023

Authors: Jian Fang, NEC Laboratories America, Inc.; Yaowen Li, NEC Laboratories America, Inc.; Philip N. Ji, NEC Laboratories America, Inc.; Ting Wang, NEC Laboratories America, Inc.

Abstract: In recent years, the widespread use of drones has led to serious concerns about safety and privacy. Drone detection using microphone arrays has proven to be a promising method. However, it is challenging for microphones to serve large-scale applications due to the issues of synchronization, complexity, and data management. Moreover, distributed acoustic sensing (DAS) using optical fibers has demonstrated its advantages in monitoring vibrations over long distances but does not have the necessary sensitivity for weak airborne acoustics. In this work, we present, to the best of our knowledge, the first fiber-optic quasi-distributed acoustic sensing demonstration for drone surveillance. We develop enhanced fiber-optic acoustic sensors (FOASs) for DAS to detect drone sound. The FOAS shows an ultra-high measured sensitivity of −101.21 re. 1rad/µPa, as well as the capability for high-fidelity speech recovery. A single DAS can interrogate a series of FOASs over a long distance via optical fiber, enabling intrinsic synchronization and centralized signal processing.We demonstrate the field test of drone detection and localization by concatenating four FOASs as DAS. Both the waveforms and spectral features of the drone sound are recognized. With acoustic field mapping and data fusion, accurate drone localization is achieved with a root-mean-square error (RMSE) of 1.47 degrees. This approach holds great potential in large-scale sound detection applications, such as drone detection or city event monitoring.

Publication Link: https://ieeexplore.ieee.org/document/9896929

Ambient Noise based Weakly Supervised Manhole Localization Methods over Deployed Fiber Networks

February 1, 2023/0 Comments/in Publications/by NEC Labs America

Publication Date: 2/1/2023

Event: Optics Express

Reference: 31(6):9591-9607, 2023

Authors: Alexander Bukharin, NEC Laboratories America, Inc., Georgia Institute of Technology; Shaobo Han, NEC Laboratories America, Inc.; Yuheng Chen, NEC Laboratories America, Inc.; Ming-Fang Huang, NEC Laboratories America, Inc.; Yue-Kai Huang, NEC Laboratories America, Inc.; Yao Xie, Georgia Institute of Technology; Ting Wang, NEC Laboratories America, Inc.

Abstract: We present a manhole localization method based on distributed fiber optic sensing and weakly supervised machine learning techniques. For the first time to our knowledge, ambient environment data is used for underground cable mapping with the promise of enhancing operational efficiency and reducing field work. To effectively accommodate the weak informativeness of ambient data, a selective data sampling scheme and an attention-based deep multiple instance classification model are adopted, which only requires weakly annotated data. The proposed approach is validated on field data collected by a fiber sensing system over multiple existing fiber networks.

Publication Link: https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-6-9591&id=527096

Optical Networking & Sensing | Publications

Utility Pole Localization by Learning From Ambient Traces on Distributed Acoustic Sensing

Real-Time Blind Source Separation with Integrated Photonics for Wireless Signals

Explore Benefits of Distributed Fiber Optic Sensing for Optical Network Service Providers

Data-driven Modelling of EDFAs by Neural Networks

Improvement of resilience of submarine networks based on fiber sensing

Field Trial of Coexistence and Simultaneous Switching of Real-time Fiber Sensing and 400GbE Supporting DCI and 5G Mobile Services

Polarization Sensing Using Polarization Rotation Matrix Eigenvalue Method

DAS over 1,007-km Hybrid Link with 10-Tb/s DP-16QAM Co-propagation using Frequency- Diverse Chirped Pulses

Drone Detection and Localization using Enhanced Fiber-Optic Acoustic Sensor and Distributed Acoustic Sensing Technology

Ambient Noise based Weakly Supervised Manhole Localization Methods over Deployed Fiber Networks

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