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Superimposed Training for Channel Estimation in FBMC-OQAM

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dc.affiliation.dptoUC3M. Departamento de Teoría de la Señal y Comunicacioneses
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Comunicacioneses
dc.contributor.authorChen Hu, Kun
dc.contributor.authorEstrada Jiménez, Juan Carlos
dc.contributor.authorFernández-Getino García, María Julia
dc.contributor.authorGarcía-Armada, Ana
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2021-09-15T11:13:21Z
dc.date.available2021-09-15T11:13:21Z
dc.date.issued2017-09-24
dc.descriptionProceedings of: 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall)en
dc.description.abstractWireless broadband communication systems are always requiring higher data rates. In order to achieve this goal, we should provide advanced schemes which are capable of improving the spectral efficiency and reusing, in a better way, the available radio spectrum resources. Filter Bank Multi-Carrier Offset Quadrature Amplitude Modulation (FBMC-OQAM) combined with Superimposed Training (ST) is a promising technique with a very high spectral efficiency. This improvement is due to the low out-of-band emissions of FBMC-OQAM, because it uses a well-designed prototype filter, and the lack of dedicated pilot tones owing to ST scheme. However, this combination is not straightforward due to the appearance of the self-interference at receiver side in FBMC-OQAM. In this paper, we provide a novel channel estimation which is capable of dealing with this self-interference in the context of combining these two techniques.en
dc.description.sponsorshipThis work has been partly supported by Spanish National Projects ELISA (TEC2014-59255-C3-3-R) and MACHINE (TSI-100102-2015-17); and also by National Secretary of Science, Technology and Innovation SENESCYT Ecuador.en
dc.format.extent5
dc.identifier.bibliographicCitationChen-Hu, K., Estrada-Jimenez, J. C., Fernandez-Getino Garcia, M. J. & Garcia Armada, A. (24-27 september, 2017). Superimposed Training for Channel Estimation in FBMC-OQAM. In: 2017 IEEE 86th Vehicular Technology Conference (VTC2017-Fall), pp- 1-5.en
dc.identifier.isbn9781509059355
dc.identifier.publicationfirstpage1
dc.identifier.publicationlastpage5
dc.identifier.publicationtitle2017 IEEE 86th Vehicular Technology Conference (VTC-Fall)en
dc.identifier.urihttps://hdl.handle.net/10016/33273
dc.identifier.uxxiCC/0000028524
dc.language.isoeng
dc.publisherIEEE
dc.relation.eventdate2017-09-24
dc.relation.eventplaceCanadáes
dc.relation.eventtitle2017 IEEE 86th Vehicular Technology Conference: VTC2017-Fall 24-27 September 2017, Toronto, Canadaen
dc.relation.projectIDGobierno de España. TEC2014-59255-C3-3-Res
dc.rights© 2017, IEEE
dc.rights.accessRightsopen accessen
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherChannel estimationen
dc.subject.otherInterferenceen
dc.subject.otherOfdmen
dc.subject.otherPrototypesen
dc.subject.otherTrainingen
dc.subject.otherFilter banksen
dc.subject.otherTime-frequency analysisen
dc.titleSuperimposed Training for Channel Estimation in FBMC-OQAMen
dc.typeconference output*
dc.type.hasVersionAM*
dspace.entity.typePublication
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