Over-the-fiber Digital Predistortion Using Reinforcement Learning

TL;DR

This paper presents the first experimental over-the-fiber training of transmitter neural networks using reinforcement learning, achieving significant bit-error-rate improvements over traditional methods.

Contribution

It introduces a novel neural network-based digital predistorter trained via reinforcement learning over fiber, outperforming conventional arcsine-based predistortion.

Findings

Up to 60% bit-error-rate reduction

First experimental over-the-fiber training of transmitter NNs

Neural network predistorter outperforms traditional methods

Abstract

We demonstrate, for the first time, experimental over-the-fiber training of transmitter neural networks (NNs) using reinforcement learning. Optical back-to-back training of a novel NN-based digital predistorter outperforms arcsine-based predistortion with up to 60\% bit-error-rate reduction.