Revisiting Multi-Step Nonlinearity Compensation with Machine Learning

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.

4 pages, 3 figures, This is a preprint of a paper submitted to the 2019 European Conference on Optical Communication