Eduardo Mateo NEC Labs America

Eduardo Mateo

Senior Researcher

Optical Networking & Sensing

Posts

Machine Learning Model for EDFA Predicting SHB Effects

Experiments show that machine learning model of an EDFA is capable of modelling spectral hole burning effects accurately. As a result, it significantly outperforms black-box models that neglect inhomogeneous effects. Model achieves a record average RMSE of 0.0165 dB between the model predictions and measurements.

NEC Labs America Team Attends the 2024 European Conference on Optical Communication (ECOC) in Frankfurt, Germany

Our optical networking & sending team has arrived in Frankfurt for the 2024 European Conference on Optical Communication (ECOC)  and is excited to present many papers and tutorials this week. Please follow this page and on our social media channels for updates.

First Field Trial of Hybrid Fiber Sensing with Data Transmission Resulting in Enhanced Sensing Sensitivity and Spatial Resolution

Optical fiber cables, initially designed for telecommunications, are increasingly repurposed for environmental monitoring using distributed fiber sensing technologies [1,2]. Distributed acoustic sensing (DAS) based on phase optical time domain reflectometry (?-OTDR) of Rayleigh backscatter enables various applications including traffic monitoring [3], railway [4] and perimeter intrusion detection [5] and cable damage detection [6], etc. The sensing range of DAS is typically limited to several tens of kilometers due to low optical signal-to-noise (OSNR) of the received backscatter. Additionally, compatibility of DAS with existing fiber infrastructure is hindered by the unidirectional operation of inline amplifiers with isolators. An alternative approach based on forward transmission was recently proposed [7, 8], which involves probing an optical fiber with a continuous wave (CW) signal and measuring either changes in received phase or the state of polarization (SOP) to detect cumulative vibration-induced strain. Unlike backscatter measurement, forward transmissions methods have longer sensing range due to higher OSNR, and is compatible with existing telecom infrastructure. However, potential challenges include limited localization accuracy, and low number of simultaneous events that can be discriminated and localized [7]. In this paper, we propose a new concept of “hybrid fiber sensing” for long-haul DWDM networks where the repeater node architecture combines DAS with forward-phase sensing (FPS), enhancing sensitivity by 32%. This approach achieves a multi-span, fine-resolution fiber sensing system. The FPS method detects vibration anomalies and coarsely localizes its position to within a fiber span. A segmented DAS then refines the position estimate and provides a precise waveform measurement. Consequently, the special resolution improves from one fiber span of 80 km to 4 m. Our scheme is validated on a test bed comprising lab spools and field fibers, demonstrating the capability to detect and monitor field construction while simultaneously supporting full C-band 400-Gb/s real-time (RT) data transmission.

Data-driven Modelling of EDFAs by Neural Networks

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

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.

Polarization Sensing Using Polarization Rotation Matrix Eigenvalue Method

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.

Guided Acoustic Brillouin Scattering Measurements In Optical Communication Fibers

Guided acoustic Brillouin (GAWBS) noise is measured using a novel, homodyne measurement technique for four commonly used fibers in long-distance optical transmission systems. The measurements are made with single spans and then shown to be consistent with separate multi-span long-distance measurements. The inverse dependence of the GAWBS noise on the fiber effective area is confirmed by comparing different fibers with the effective area varying between 80 µm2 and 150 µm2. The line broadening effect of the coating is observed, and the correlation between the width of the GAWBS peaks to the acoustic mode profile is confirmed. An extensive model of the GAWBS noise in long-distance fibers is presented, including corrections to some commonly repeated mistakes in previous reports. It is established through the model and verified with the measurements that the depolarized scattering caused by TR2m modes contributes twice as much to the optical noise in the orthogonal polarization to the original source, as it does to the noise in parallel polarization. Using this relationship, the polarized and depolarized contributions to the measured GAWBS noise is separated for the first time. As a result, a direct comparison between the theory and the measured GAWBS noise spectrum is shown for the first time with excellent agreement. It is confirmed that the total GAWBS noise can be calculated from fiber parameters under certain assumptions. It is predicted that the level of depolarized GAWBS noise created by the fiber may depend on the polarization diffusion length, and consequently, possible ways to reduce GAWBS noise are proposed. Using the developed theory, dependence of GAWBS noise on the location of the core is calculated to show that multi-core fibers would have a similar level of GAWBS noise no matter where their cores are positioned.

Estimation of Core-Cladding Concentricity Error From GAWBS Noise Spectrum

CCCE in a 60-km fiber is estimated from its GAWBS noise spectrum by comparing the TR 1m modes with the R 0m modes. The estimated CCCE value 0.73 μm is consistent with conventional measurements of 0.6–0.8 μm.

Field and lab experimental demonstration of nonlinear impairment compensation using neural networks

Fiber nonlinearity is one of the major limitations to the achievable capacity in long distance fiber optic transmission systems. Nonlinear impairments are determined by the signal pattern and the transmission system parameters. Deterministic algorithms based on approximating the nonlinear Schrodinger equation through digital back propagation, or a single step approach based on perturbation methods have been demonstrated, however, their implementation demands excessive signal processing resources, and accurate knowledge of the transmission system. A completely different approach uses machine learning algorithms to learn from the received data itself to figure out the nonlinear impairment. In this work, a single-step, system agnostic nonlinearity compensation algorithm based on a neural network is proposed to pre-distort symbols at transmitter side to demonstrate ~0.6?dB Q improvement after 2800?km standard single-mode fiber transmission using 32 Gbaud signal. Without prior knowledge of the transmission system, the neural network tensor weights are constructed from training data thanks to the intra-channel cross-phase modulation and intra-channel four-wave mixing triplets used as input features.

Spectrally-Efficient 200G Probabilistically-Shaped 16QAM over 9000km Straight Line Transmission with Flexible Multiplexing Scheme

Flexible wavelength-multiplexing technique in backbone submarine networks has been deployed to accommodate the trend of variable-rate modulation formats. In this paper, we propose a new design of flexible-rate transponders in the scenario of flexible multiplexing scheme to achieve near-Shannon performance. Probabilistic-shaped (PS) M-QAM is capable of adjusting the bit rate at very finer granularity by adapting the entropy of the distribution matcher. Instead of delivering variable bit rates at the fixed baud rate, various baud rates of 200Gb/s PS-16QAM is demonstrated to fit into the flexible grid multiple 3.125GHz bandwidth. This flexible baud rate saves the limited optical bandwidth assigned by the flexible multiplexing scheme to improve bandwidth utilization. The 200G PS-16QAM signals are experimentally demonstrated over 9000km straight-line testbed to achieve 3.05b/s/Hz~5.33 b/s/Hz spectral efficiency (SE) with up to 4dB Q margin. In addition, the high baud rate signals are used for lower SE while low baud rate signals are targeting at high SE transmission to reduce the implementation penalty.