Smart optical networks enabled by performance monitoring and machine learning

The two main objectives of the project are:

(1) investigating machine learning (ML) techniques for quality of transmission (QoT) estimation and prediction in the optical layer;

(2) exploring ML methods for anomaly detection and proactive failure management at the network level.

ML-based methods for QoT estimation and prediction at the physical layer will be explored. ML techniques such as long-term short-memory (LSTM) and neural networks will be investigated for QoT prediction as ways to discover patterns in time-series and achieve dynamic and autonomous system margin control.

Start date 01/10/2021
End date 30/09/2024

Page manager Published: Sat 02 Oct 2021.