Generative adversarial networks for generating synthetic features for Wi-Fi signal quality

Detalhes bibliográficos
Autor(a) principal: Castelli, Mauro
Data de Publicação: 2021
Outros Autores: Manzoni, Luca, Espindola, Tatiane, Popovič, Aleš, De Lorenzo, Andrea
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/128519
Resumo: Castelli, M., Manzoni, L., Espindola, T., Popovič, A., & De Lorenzo, A. (2021). Generative adversarial networks for generating synthetic features for Wi-Fi signal quality. PLoS ONE, 16(11), 1-30. [e0260308]. https://doi.org/10.1371/journal.pone.0260308
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spelling Generative adversarial networks for generating synthetic features for Wi-Fi signal qualityGeneralCastelli, M., Manzoni, L., Espindola, T., Popovič, A., & De Lorenzo, A. (2021). Generative adversarial networks for generating synthetic features for Wi-Fi signal quality. PLoS ONE, 16(11), 1-30. [e0260308]. https://doi.org/10.1371/journal.pone.0260308Wireless networks are among the fundamental technologies used to connect people. Considering the constant advancements in the field, telecommunication operators must guarantee a high-quality service to keep their customer portfolio. To ensure this high-quality service, it is common to establish partnerships with specialized technology companies that deliver software services in order to monitor the networks and identify faults and respective solutions. A common barrier faced by these specialized companies is the lack of data to develop and test their products. This paper investigates the use of generative adversarial networks (GANs), which are state-of-the-art generative models, for generating synthetic telecommunication data related to Wi-Fi signal quality. We developed, trained, and compared two of the most used GAN architectures: the Vanilla GAN and the Wasserstein GAN (WGAN). Both models presented satisfactory results and were able to generate synthetic data similar to the real ones. In particular, the distribution of the synthetic data overlaps the distribution of the real data for all of the considered features. Moreover, the considered generative models can reproduce the same associations observed for the synthetic features. We chose the WGAN as the final model, but both models are suitable for addressing the problem at hand.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNCastelli, MauroManzoni, LucaEspindola, TatianePopovič, AlešDe Lorenzo, Andrea2021-11-30T23:54:33Z2021-11-232021-11-23T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article30application/pdfhttp://hdl.handle.net/10362/128519eng1932-6203PURE: 35127452https://doi.org/10.1371/journal.pone.0260308info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:08:05Zoai:run.unl.pt:10362/128519Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:46:19.562505Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Generative adversarial networks for generating synthetic features for Wi-Fi signal quality
title Generative adversarial networks for generating synthetic features for Wi-Fi signal quality
spellingShingle Generative adversarial networks for generating synthetic features for Wi-Fi signal quality
Castelli, Mauro
General
title_short Generative adversarial networks for generating synthetic features for Wi-Fi signal quality
title_full Generative adversarial networks for generating synthetic features for Wi-Fi signal quality
title_fullStr Generative adversarial networks for generating synthetic features for Wi-Fi signal quality
title_full_unstemmed Generative adversarial networks for generating synthetic features for Wi-Fi signal quality
title_sort Generative adversarial networks for generating synthetic features for Wi-Fi signal quality
author Castelli, Mauro
author_facet Castelli, Mauro
Manzoni, Luca
Espindola, Tatiane
Popovič, Aleš
De Lorenzo, Andrea
author_role author
author2 Manzoni, Luca
Espindola, Tatiane
Popovič, Aleš
De Lorenzo, Andrea
author2_role author
author
author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Castelli, Mauro
Manzoni, Luca
Espindola, Tatiane
Popovič, Aleš
De Lorenzo, Andrea
dc.subject.por.fl_str_mv General
topic General
description Castelli, M., Manzoni, L., Espindola, T., Popovič, A., & De Lorenzo, A. (2021). Generative adversarial networks for generating synthetic features for Wi-Fi signal quality. PLoS ONE, 16(11), 1-30. [e0260308]. https://doi.org/10.1371/journal.pone.0260308
publishDate 2021
dc.date.none.fl_str_mv 2021-11-30T23:54:33Z
2021-11-23
2021-11-23T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/128519
url http://hdl.handle.net/10362/128519
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1932-6203
PURE: 35127452
https://doi.org/10.1371/journal.pone.0260308
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 30
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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