Nonlinear Interference Mitigation via Deep Neural Networks

TL;DR

This paper introduces a neural network-based method for digital backpropagation in fiber-optic communications, achieving significant complexity reduction for long-distance links.

Contribution

It presents a novel deep neural network approach to implement digital backpropagation more efficiently than traditional methods.

Findings

Reduces computational complexity of DBP

Effective for 32x100 km fiber-optic links

Maintains performance with less resource use

Abstract

A neural-network-based approach is presented to efficiently implement digital backpropagation (DBP). For a 32x100 km fiber-optic link, the resulting "learned" DBP significantly reduces the complexity compared to conventional DBP implementations.