30 citations · 184 across the 34 of their papers we have counts for
6 papers · 1 filter
Capitalizing on Next-Generation Optical Communication Systems with Proactive Multi-Period Network Planning
Jasper Müller, Sai Kireet Patri, Gabriele Di Rosa +3
Optical transport network operators typically follow a pay-as-you-grow strategy for their network deployment. We propose a proactive multi-period planning approach based on heurist…
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…