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  • European Conference on Optical Communication (ECOC) 2022
  • Technical Digest Series (Optica Publishing Group, 2022),
  • paper We1C.4

Learning for Perturbation-Based Fiber Nonlinearity Compensation

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Abstract

Several machine learning inspired methods for perturbation-based fiber n onlinearity (PBNLC) compensation have been presented in recent literature. We critically revisit acclaimed benefits of those over non-learned methods. Numerical results suggest that learned linear processing of perturbation triplets of PB-NLC is preferable over feedforward neural-network solutions.

© 2022 The Author(s)

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