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Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation
Published 25 Jan 2020 in eess.SP, cs.IT, cs.LG, math.IT, and stat.ML | (2001.09277v1)
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.
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