We propose extending the LOGO strategy for launch power settings to multi-band scenarios, maintaining low complexity while addressing key inter-band nonlinear effects and accurate amplifier models. This methodology simplifies multi-band optical multiplex section control, providing an immediate, descriptive estimation of optimized launch power.
We demonstrate a method for measuring the backscatter coefficient of hollow-core fibre (HCF), and show the feasibility of distributed acoustic sensing (DAS) with simultaneous 9.6-Tb/s DWDM transmission over a 1.6-km field-deployed HCF cable.
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.
We propose a transceiver back-to-back BER-OSNR characterization method that requires only a single VOA; it leverages the receiver SNR degradation caused by received power attenuation. Experiments using commercial transceivers show that the measurement error is less than 0.2 dB in the Q-factor.
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.
We propose methods and an architecture to conduct measurements and optimize newly installed optical fiber line systems semi-automatically using integrated physics-aware technologies in a data center interconnection (DCI) transmission scenario. We demonstrate, for the first time to our knowledge, digital longitudinal monitoring (DLM) and optical line system (OLS) physical parameter calibration working together in real-time to extract physical link parameters for fast optical fiber line systems provisioning. Our methodology has the following advantages over traditional design: a minimized footprint at user sites, accurate estimation of the necessary optical network characteristics via complementary telemetry technologies, and the capability to conduct all operation work remotely. The last feature is crucial, as it enables remote operation to implement network design settings for immediate response to quality of transmission (QoT) degradation and reversion in the case of unforeseen problems. We successfully performed semi-automatic line system provisioning over field fiber network facilities at Duke University, Durham, North Carolina. The tasks of parameter retrieval, equipment setting optimization, and system setup/provisioning were completed within 1 h. The field operation was supervised by on-duty personnel who could access the system remotely from different time zones. By comparing Q-factor estimates calculated from the extracted link parameters with measured results from 400G transceivers, we confirmed that our methodology has a reduction in the QoT prediction errors ( 0.3 dB) over existing designs ( 0.6 dB). ©
The GNPy quality-of-transmission estimator has undergone improvements and rigorous experimental validation in a C+L multiband transmission scenario. This includes the incorporation of a disaggregated generalized Gaussian noise model, along with advanced modeling of amplifiers and transceivers. The recently proposed implementation demonstrates notable enhancements, offering highly accurate GSNR predictions on commercial C+L-band equipment while significantly reducing computation time.
A control architecture for a partially disaggregated optical network is proposed using a GNPy-based digital twin for QoT estimation. The proposed implementation enables soft failure mitigation by autonomously adjusting the amplifier working points.
We propose a deep learning algorithm trained on varied spectral loads and EDFA working points to generate a digital twin of an optical line system able to optimize line control and to enhance OSNR predictions.
The ever-increasing demand for data traffic in recent decades has pushed network operators to give importance to the aspect of infrastructure control to facilitate its scalability and maximize its capacity. A generic lightpath (LP) is deployed starting from a traffic request between a given pair of nodes in a network. LPs are operated in the network based on an estimate of the quality of transmission (QoT), which is derived from the physical layer characteristics of a selected route. Regardless of the model used to estimate QoT, it is necessary to calibrate themodel to maximize its accuracy and define minimum design margins. The model calibration process depends significantly on the type of data that can be collected in the field (i.e., type of metric, resolution) and therefore on the available monitoring devices. In this work, a systematic evaluation of the QoT estimation is carried out on a multi-span erbium-doped-fiber-amplified optical line system (OLS) using in the first case only total power monitors and in the second experimentally emulating optical channel monitors (OCMs). Given the type of monitoring devices available, three different physical models are calibrated, and six optimization methods are used to define the optimal configuration of the target gain and tilt parameters of the optical amplifiers, jointly optimizing the working point of all amplifiers (global approach) or proceeding span by span (local approach). Subsequently, the OLS was set in each configuration obtained, and the generalized signal-to-noise ratio (GSNR) profile was measured at the end.
