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Deep Learning Based Digital Back Propagation with Polarization State Rotation & Phase Noise Invariance

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Abstract

A new deep learning training method for digital back propagation (DBP) is introduced. It is invariant to polarization state rotation and phase noise. Applying the method one gains more than 1 dB over standard DBP.

© 2020 The Author(s)

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