Abstract

The estimation of the quality of transmission (QoT) in optical systems with machine learning (ML) has recently been the focus of a large body of research. We discuss the sources of inaccuracy in QoT estimation in general; we propose a taxonomy for ML-aided QoT estimation; we briefly review ML-aided optical performance monitoring, a tightly related topic; and we review and compare all recently published ML-aided QoT articles.

© 2021 Optical Society of America

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