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An autoencoder-based solution for IQ constellation analysis
dc.contributor.author | Ruiz Ramírez, Marc |
dc.contributor.author | Morales López, Javier |
dc.contributor.author | Sequeira, Diogo Gonçalo |
dc.contributor.author | Velasco Esteban, Luis Domingo |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors |
dc.contributor.other | Universitat Politècnica de Catalunya. Doctorat en Enginyeria Electrònica |
dc.contributor.other | Universitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors |
dc.date.accessioned | 2022-02-07T10:12:41Z |
dc.date.available | 2022-02-07T10:12:41Z |
dc.date.issued | 2021 |
dc.identifier.citation | Ruiz, 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.isbn | 978-1-6654-3868-1 |
dc.identifier.uri | http://hdl.handle.net/2117/361753 |
dc.description.abstract | A 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.sponsorship | This 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.extent | 4 p. |
dc.language.iso | eng |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telecomunicació òptica |
dc.subject.lcsh | Machine learning |
dc.subject.lcsh | Data compression (Computer science) |
dc.subject.lcsh | Optical fiber communication |
dc.subject.other | Measurement |
dc.subject.other | Europe |
dc.subject.other | Predictive models |
dc.subject.other | Data models |
dc.subject.other | Numerical models |
dc.title | An autoencoder-based solution for IQ constellation analysis |
dc.type | Conference report |
dc.subject.lemac | Aprenentatge automàtic |
dc.subject.lemac | Dades -- Compressió (Informàtica) |
dc.subject.lemac | Comunicació per fibra òptica |
dc.contributor.group | Universitat Politècnica de Catalunya. GCO - Grup de Comunicacions Òptiques |
dc.identifier.doi | 10.1109/ECOC52684.2021.9606175 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/9606175 |
dc.rights.access | Open Access |
local.identifier.drac | 32361136 |
dc.description.version | Postprint (author's final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/H2020/813144/EU/REAL-time monitoring and mitigation of nonlinear effects in optical NETworks/REAL-NET |
dc.relation.projectid | info: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.author | Ruiz, M.; Morales, J.; Sequeira, D.; Velasco, L. |
local.citation.contributor | European Conference on Optical Communication |
local.citation.publicationName | European Conference on Optical Communication, ECOC 2021: Bordeaux, France, September 13-16, 2021 |
local.citation.startingPage | 1 |
local.citation.endingPage | 4 |
dc.relation.dataset | https://doi.org/10.34810/data146 |