48 citations · 93 across the 3 of their papers we have counts for
4 papers · 1 filter
Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation
Rick M. Bütler, Christian Häger, Henry D. Pfister +2
In this paper, we propose a model-based machine-learning approach for dual-polarization systems by parameterizing the split-step Fourier method for the Manakov-PMD equation. The re…
Revisiting Efficient Multi-Step Nonlinearity Compensation with Machine Learning: An Experimental Demonstration
Vinícius Oliari, Sebastiaan Goossens, Christian Häger +7
Efficient nonlinearity compensation in fiber-optic communication systems is considered a key element to go beyond the "capacity crunch''. One guiding principle for previous work on…
Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation
Christian Häger, Henry D. Pfister, Rick M. Bütler +2
We propose a model-based machine-learning approach for polarization-multiplexed systems by parameterizing the split-step method for the Manakov-PMD equation. This approach performs…
Revisiting Multi-Step Nonlinearity Compensation with Machine Learning
Christian Häger, Henry D. Pfister, Rick M. Bütler +2
For the efficient compensation of fiber nonlinearity, one of the guiding principles appears to be: fewer steps are better and more efficient. We challenge this assumption and show…