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dc.contributor.authorLópez Bueno, David
dc.contributor.authorPham, Thi Quynh Anh
dc.contributor.authorMontoro López, Gabriel
dc.contributor.authorGilabert Pinal, Pere Lluís
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2020-05-04T06:01:36Z
dc.date.issued2019
dc.identifier.citationLópez, D. [et al.]. Linealización digital de transmisores mediante redes neuronales no lineales. A: Simposium Nacional de la Unión Científica Internacional de Radio. "Proceedings URSI". 2019.
dc.identifier.isbn978-84-09-12961-4
dc.identifier.otherhttps://zenodo.org/record/3678089#.XqbANpmxU2y
dc.identifier.urihttp://hdl.handle.net/2117/186053
dc.description.abstractThis paper presents an overview on how the artificial neural networks (ANN) are applied to digitally linearize modern transmitters. The use of nonlinear ANNs is intended to either assist or replace the traditional crest factor reduction (CFR) and digital predistortion (DPD) building blocks, and benefit from their inherently good approximation capabilities and reduced hardware complexity when targeting complex transceiver scenarios such as those present in 5G. There is not a universal procedure to set up the best ANN given a specific application. However, in this paper some design considerations which have been experimentally validated in the literature will be summarized both considering single-antenna and multi-antenna transmitters. Finally, some principles in the selection of ANN parameters for nonlinear modeling will be showcased by using asimulation test bench that employs measured data from a strongly non-linear GaN PA operated with wideband signals.
dc.description.sponsorshipAgradecemos el soporte y financiación recibidos por el Gobierno de España (MICINN) y FEDER en el marco de los proyectos TEC2017-83343-C4-2-R y RTI2018-099841-B-I00, y por la Generalitat de Catalunya bajo las ayudas 2017 SGR 813 y 2017 SGR 891.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació
dc.subject.lcshNeural networks (Computer science)
dc.subject.otherTransmisores
dc.subject.otherRedes neuronales.
dc.titleLinealización digital de transmisores mediante redes neuronales no lineales
dc.typeConference report
dc.subject.lemacXarxes neuronals (Informàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. CSC - Components and Systems for Communications Research Group
dc.description.peerreviewedPeer Reviewed
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac26517618
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/FEDER/TEC2017/88343-C4-2-R
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/FEDER/RTI2018-099841-B-I00
dc.relation.projectidinfo:eu-repo/grantAgreement/GENCAT/AGAUR/2017/SGR813
dc.relation.projectidinfo:eu-repo/grantAgreement/GENCAT/AGAUR/2017/SGR891
dc.date.lift10000-01-01
local.citation.authorLópez, D.; Pham, T.; Montoro, G.; Gilabert, Pere L.
local.citation.contributorSimposium Nacional de la Unión Científica Internacional de Radio
local.citation.publicationNameProceedings URSI


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