Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation

Autor:	Häger, Christian, Pfister, Henry D., Bütler, Rick M., Liga, Gabriele, Alvarado, Alex
Rok vydání:	2020
Předmět:	Electrical Engineering and Systems Science - Signal Processing Computer Science - Information Theory Computer Science - Machine Learning Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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. Comment: 3 pages, 2 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2001.09277 Zobrazit plný text záznamu View this record from Arxiv