Deep Learning Based Digital Back Propagation with Polarization State Rotation & Phase Noise Invariance
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.
Publication status
publishedExternal links
Book title
Optical Fiber Communication Conference (OFC) 2020Journal / series
OSA Technical DigestPages / Article No.
Publisher
OSA PublishingEvent
Organisational unit
02635 - Institut für Elektromagnetische Felder / Electromagnetic Fields Laboratory03974 - Leuthold, Juerg / Leuthold, Juerg
Funding
670478 - Plasmonic-Silicon-Organic Hybrid – a Universal Platform for THz Communications (EC)
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