Domain Adaptation: the Key Enabler of Neural Network Equalizers in Coherent Optical Systems

Abstract

We introduce the domain adaptation and randomization approach for calibrating neural network-based equalizers for real transmissions, using synthetic data. The approach renders up to 99\% training process reduction, which we demonstrate in three experimental setups.

Paper Accepted at OFC 2022