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Workshop on machine learning in optical communication systems

25 mars à 14h00 - 17h30 CET

In this joint Digicosme/Gdr-ISIS workshop, we are interested in covering an overview of machine learning (ML) algorithms and applications for optical communication systems and networks. ML is based on an idea that synthetic or real data can be used to train systems in order to enable them to make decisions or predictions on new unknown data. Most ML algorithms deal with two tasks: regression and classification (or clustering). Although ML is not a new field, recent important increases in computational power and access to abundant quantities of data contributed to the advent of novel ML methods applied in several fields. Researchers in the field of optical communications are no strangers to regression and classification problems tackled with probability theory and an understanding of the problem’s underlying physics. However, as the sources of transmission impairments are becoming more numerous and complex for high-rate links and networks, explicit characterizations of these impairments, their mitigation and the prediction of their impact on the quality of transmission become hard to analyze. As a consequence, applications of ML techniques range from compensation of fiber non linearity and transceiver imperfections to optical performance monitoring and software-defined networking. Indeed, besides the developments related to the physical layer, optical network architectures and operations are undergoing an important evolution towards adaptive provisioning of resources and fast discovery of faults to minimize system outage. Extracting patterns from numerous physical-layer and network-layer parameters naturally calls for ML algorithms. Through a coverage of ML applications in optical communications and networking, we hope to provide a better understanding of the most suitable use cases of ML where it can play a unique role.  

 

Registration

Please register using the following Google Form. An ics calendar file will be provided so you can register the event in your agenda.  
 
 

Contacts

Elie AWWAD elie.awwad@telecom-paris.fr
Catherine LEPERS catherine.lepers@telecom-sudparis.eu

 

Program

2:00pm – 2:05pm Introduction – Catherine Lepers & Elie Awwad
2:05pm – 2:45pm Machine learning-aided quality of transmission (QoT) estimation” – Yvan Pointurier, Huawei France
2:45pm – 3:15pm A novel data augmentation technique to reduce the complexity of receiver-based DSP in optical telecommunications” – Vladislav Neskorniuk, Aston Institute of Photonic Technologies
3:15pm – 3:45pm The Potential of Artificial Intelligence (AI) in Optical Transport Network” – Ahmed Triki, Orange Labs
3:45pm – 4:00pm Break
4:00pm – 4:40pm Design of Submarine Optical Fiber Links Optimised through Reinforcement Learning” – Maria Ionescu, Nokia Bell Labs France
4:40pm – 5:10pm Efficient equalization in nonlinear fiber-optic communications using a convolutional recurrent neural network” – Abtin Shahkarami, Télécom Paris
5:10pm-5:20pm Conclusion – Catherine Lepers & Elie Awwad

Détails

Date:
25 mars
Heure :
14h00 - 17h30 CET
Catégorie d’évènement:
https://digicosme.cnrs.fr/workshop-on-machine-learning-in-optical-communication-systems/

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