Show simple item record

dc.contributor.authorRuiz Ramírez, Marc
dc.contributor.authorMorales López, Javier
dc.contributor.authorSequeira, Diogo Gonçalo
dc.contributor.authorVelasco Esteban, Luis Domingo
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Enginyeria Electrònica
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors
dc.date.accessioned2022-02-07T10:12:41Z
dc.date.available2022-02-07T10:12:41Z
dc.date.issued2021
dc.identifier.citationRuiz, M. [et al.]. An autoencoder-based solution for IQ constellation analysis. A: European Conference on Optical Communication. "European Conference on Optical Communication, ECOC 2021: Bordeaux, France, September 13-16, 2021". Institute of Electrical and Electronics Engineers (IEEE), 2021, p. 1-4. ISBN 978-1-6654-3868-1. DOI 10.1109/ECOC52684.2021.9606175.
dc.identifier.isbn978-1-6654-3868-1
dc.identifier.urihttp://hdl.handle.net/2117/361753
dc.description.abstractA method for IQ constellation analysis based on Autoencoders is proposed. Exhaustive numerical results show accurate physical metric prediction and large data compression, while providing useful model explainability.
dc.description.sponsorshipThis work has been partially supported by the EC through the MSC REAL-NET project (G.A. 813144), by the AEI/FEDER through the TWINS project (TEC2017- 90097-R), and by the ICREA institution.
dc.format.extent4 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telecomunicació òptica
dc.subject.lcshMachine learning
dc.subject.lcshData compression (Computer science)
dc.subject.lcshOptical fiber communication
dc.subject.otherMeasurement
dc.subject.otherEurope
dc.subject.otherPredictive models
dc.subject.otherData models
dc.subject.otherNumerical models
dc.titleAn autoencoder-based solution for IQ constellation analysis
dc.typeConference report
dc.subject.lemacAprenentatge automàtic
dc.subject.lemacDades -- Compressió (Informàtica)
dc.subject.lemacComunicació per fibra òptica
dc.contributor.groupUniversitat Politècnica de Catalunya. GCO - Grup de Comunicacions Òptiques
dc.identifier.doi10.1109/ECOC52684.2021.9606175
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9606175
dc.rights.accessOpen Access
local.identifier.drac32361136
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/813144/EU/REAL-time monitoring and mitigation of nonlinear effects in optical NETworks/REAL-NET
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TEC2017-90097-R/ES/COGNITIVE 5G APPLICATION-AWARE OPTICAL METRO NETWORKS INTEGRATING MONITORING, DATA ANALYTICS AND OPTIMIZATION/
local.citation.authorRuiz, M.; Morales, J.; Sequeira, D.; Velasco, L.
local.citation.contributorEuropean Conference on Optical Communication
local.citation.publicationNameEuropean Conference on Optical Communication, ECOC 2021: Bordeaux, France, September 13-16, 2021
local.citation.startingPage1
local.citation.endingPage4
dc.relation.datasethttps://doi.org/10.34810/data146


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record