Revisiting Multi-Step Nonlinearity Compensation with Machine Learning

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Abstract

For the efficient compensation of fiber nonlinearity, one of the guiding principles appears to be: fewer steps are better and more efficient. We challenge this assumption and show that carefully designed multi-step approaches can lead to better performance-complexity trade-offs than their few-step counterparts.

Abstract (translated by Google)

URL

http://arxiv.org/abs/1904.09807

PDF

http://arxiv.org/pdf/1904.09807