H\"ager, Christian

1paper

1 Paper

5.1SPApr 22, 2019
Revisiting Multi-Step Nonlinearity Compensation with Machine Learning

Christian Häger, Henry D. Pfister, Rick M. Bütler et al.

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.