Applications of the OCATA Optical Layer Digital Twin

Operator’s optical networks are a core infrastructure and key-enabler of today’s hyper-connected society as most of the Internet data traffic is transferred overoptical fiber networks. Data traffic volumes are experiencing rest-less growth as Internet-services are reaching increasing demand and capacity-hungry applicationsare arising (e.g., industry 4.0 applications). In view of this, constant innovation is required in optical networks to accommodate the requested capacity while minimizing the cost.In this scenario, digital twins (DTs) – intended as a combination of models self-adjusting with their physical counterpart and of algorithms acting on the network for specific applications – are being proposed as a solution for: 1) maximizing the transport capacity by reducing the network margins; 2) pave the way towards optical network automation.The main objective of this PhD Thesis is to improve network operation based on the use of DTs algorithms and models for failure management, lightpath provisioning and optical amplifier control. To achieve this goal, different machine learning (ML) algorithms were investigated and the capabilities of the optical layer DT called OCATA were extended. This main goal is achieved by the following three specific goals:1. Applications of Optical Layer DT During Network Operation. The OCATA capabilities are extended for quality of transmission (QoT) estimation and failure management. Tailor-made features are extracted from IQ constellation samples, which show correlations with QoT metrics and with failures-induced signal degradations. Next, specific ML-based models and algorithms for QoT estimation, soft-failure detection, identification and severity estimation are proposed. Results from both simulation and experiments show noticeable accuracy on the estimation of QoT and on the prediction of failures affecting the transmitter, optical filters and amplifiers. Furthermore, this approach was confirmed also for detecting and identifying spectrum anomalies.2. Applications of Optical Layer DT for Lightpath Provisioning. OCATA capabilities are extended for modulation formats besides 16-quadrature amplitudemodulation (QAM) and for digital subcarrier multiplexing signals (DSCM). Firstly, an algorithm for lightpath provisioning is proposed and evaluated basedon simulations. Secondly, I experimentally evaluate its accuracy to predict the impact of optical filtering penalties. The simulations show an overall highaccuracy for different signal formats and demonstrate their viability for lightpath provisioning. Moreover, the models showed the most advantageous trade-offbetween accuracy and execution time when compared with other existing methods. Finally, the experimental results demonstrate the feasibility of implementing such models to perform quality of transmission estimation for DSCM signals.3. Application of Optical Layer DT for Amplifier Control. DT models were designed to assist a network controller in performing informed decisions when re-configuring dynamically optical amplifiers under varying channel loadings. Experimental characterization processes were performed on pluggable EDFAs.Then, ML models based on deep learning (DL) and ensemble methods were compared in terms of accuracy and computation speed. After time-consuming hyper parameter optimization procedures, DL models showed to achieve both the best performance on the training data set and the best generalizability onunknown dataset. Furthermore, it was shown that substantial generalization error reduction can be achieved employing transfer learning techniques.