Publication:

From MFN to SFN: Performance Prediction Through Machine Learning

Date

2022
Journal article
https://doi.org/10.1109/TBC.2021.3132804
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dc.contributor.authorGonzalez, Claudia Carballo
dc.contributor.authorPupo, Ernesto Fontes
dc.contributor.authorRuisanchez, Dariel Pereira
dc.contributor.authorMuroni, Maurizio
dc.contributor.authorPlets, David
dc.contributor.imecauthorPlets, David
dc.contributor.orcidimecPlets, David::0000-0002-8879-5076
dc.date.accessioned2022-03-11T11:30:06Z
dc.date.available2021-12-29T02:06:42Z
dc.date.available2022-03-11T11:30:06Z
dc.date.embargo2022-03-31
dc.date.issued2022
dc.description.wosFundingTextThis work was supported in part by the Department of Electronic Engineering (DIEE/UdR CNIT), University of Cagliari, Cagliari, Italy; in part by the LACETEL, Research and Development Telecommunication Institute, Havana, Cuba; in part by the Department of Information Technology, Ghent University, Belgium; and in part by the Department of Computer Engineering and CITIC Research Center, A Coruna, Spain.
dc.identifier.doi10.1109/TBC.2021.3132804
dc.identifier.issn0018-9316
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/38684
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.source.beginpage180
dc.source.endpage190
dc.source.issue1
dc.source.journalIEEE TRANSACTIONS ON BROADCASTING
dc.source.numberofpages11
dc.source.volume68
dc.subject.keywordsSINGLE-FREQUENCY NETWORKS
dc.subject.keywordsALGORITHM
dc.subject.keywordsSELECTION
dc.subject.keywordsMODELS
dc.title

From MFN to SFN: Performance Prediction Through Machine Learning

dc.typeJournal article
dspace.entity.typePublication
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