376 citations · 1.2k across the 26 of their papers we have counts for
9 papers · 1 filter
On the Benefits of Rate-Adaptive Transceivers: A Network Planning Study
Jasper Müller, Gabriele Di Rosa, Tobias Fehenberger +4
Flexible-grid Elastic Optical Networks (EONs) have been widely deployed in recent years to support the growing demand for bandwidth-intensive applications. To address this cost-eff…
QoT estimation using EGN-assisted machine learning for multi-period network planning
Jasper Müller, Sai Kireet Patri, Tobias Fehenberger +3
The rapidly growing traffic demands in fiber-optical networks require flexibility and accuracy in configuring lightpaths, for which fast and accurate quality of transmission (QoT)…
Multi-Wavelength Transponders for High-capacity Optical Networks: A Physical-layer-aware Network Planning Study
Jasper Müller, Ognjen Jovanovic, Tobias Fehenberger +3
Continued cost- and power-efficient capacity scaling in optical networks is imperative to keep pace with ever-increasing traffic demands. In this paper, we investigate multi-wavele…
Comparison of Single-Wavelength and Multi-Wavelength Transponders in a Physical-layer-aware Network Planning Study
Jasper Müller, Ognjen Jovanovic, Carmen Mas-Machuca +3
Based on suitable system architectures and realistic specifications, transmit OSNR penalties and spectral constraints of multi-wavelength transponders are identified and analyzed i…
Experimental Demonstration of ML-Based DWDM System Margin Estimation
Jasper Müller, Frank Slyne, Kaida Kaeval +6
SNR margins between partially and fully loaded DWDM systems are estimated without detailed knowledge of the network. The ML model, trained on simulation data, achieves accurate pre…
A QoT Estimation Method using EGN-assisted Machine Learning for Network Planning Applications
Jasper Müller, Sai Kireet Patri, Tobias Fehenberger +3
An ML model based on precomputed per-channel SCI is proposed. Due to its superior accuracy over closed-form GN, an average SNR gain of 1.1 dB in an end-to-end link optimization and…
Estimating Quality of Transmission in a Live Production Network using Machine Learning
Jasper Müller, Tobias Fehenberger, Sai Kireet Patri +4
We demonstrate QoT estimation in a live network utilizing neural networks trained on synthetic data spanning a large parameter space. The ML-model predicts the measured lightpath p…
Black-Box Assessment of Optical Spectrum Services
Kaida Kaeval, Jörg-Peter Elbers, Klaus Grobe +4
A spectral sweep process is introduced to discover performance issues in optical spectrum services. We detect filtering penalty, spectral ripple/tilt and channel crosstalk in field…
QoT Assessment of the Optical Spectrum as a Service in Disaggregated Network Scenarios
Kaida Kaeval, Tobias Fehenberger, Jim Zou +6
The potential to operate third-party terminals over multi-domain transparent optical networks attracts operators and customers to implement Optical Spectrum as a Service (OSaaS). A…