Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation
arXiv:2001.09277
Abstract
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 hardware-friendly DBP and distributed PMD compensation with performance close to the PMD-free case.
3 pages, 2 figures