Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Deep learning-based real-time analysis of lightpath optical constellations [Invited]

Not Accessible

Your library or personal account may give you access

Abstract

Optical network automation requires accurate physical layer models, not only for provisioning but also for real-time analysis. In particular, in-phase (I) and quadrature (Q) constellation analysis enables deep understanding of the characteristics of optical connections (lightpaths), e.g., their length. In this paper, we present methods for modeling lightpaths based on deep learning. Specifically, we propose using autoencoders (AEs) and deep neural networks. Models are trained and composed in a sandbox domain with the information received from the network controller and sent to the node agent that uses them to compare the features extracted from the received signal and the expected features returned by the models. We investigate two different use cases for lightpath analysis focused on lightpath length and optical signal power. The results show a remarkable accuracy for the lightpath modeling and length prediction and a noticeable performance of the AEs for unsupervised IQ constellation feature extraction and relevance analysis.

© 2022 Optica Publishing Group

Full Article  |  PDF Article
More Like This
Machine-learning-based anomaly detection in optical fiber monitoring

Khouloud Abdelli, Joo Yeon Cho, Florian Azendorf, Helmut Griesser, Carsten Tropschug, and Stephan Pachnicke
J. Opt. Commun. Netw. 14(5) 365-375 (2022)

Evaluation of probabilistic constellation shaping performance in Flex Grid over multicore fiber dynamic optical backbone networks [Invited]

Jordi Perelló, Joan M. Gené, and Salvatore Spadaro
J. Opt. Commun. Netw. 14(5) B1-B10 (2022)

Optical network security management: requirements, architecture, and efficient machine learning models for detection of evolving threats [Invited]

Marija Furdek, Carlos Natalino, Andrea Di Giglio, and Marco Schiano
J. Opt. Commun. Netw. 13(2) A144-A155 (2021)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (16)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Tables (4)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (1)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2022 | Optica Publishing Group. All Rights Reserved