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Low-rank channel estimation for mm-Wave multiple antenna systems using joint spatio-temporal covariance matrix

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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.authorSlock, Dirk T. M.
dc.contributor.authorGarcía-Armada, Ana
dc.contributor.funderMinisterio de Ciencia e Innovación (España)es
dc.date.accessioned2023-02-22T08:34:10Z
dc.date.available2023-02-22T08:34:10Z
dc.date.issued2019-01-20
dc.descriptionProceedings of: 2019 IEEE International Conference on Communications Workshops (ICC Workshops), 20-24 May 2019, Shanghai, China.en
dc.description.abstractMillimeter-Wave (mm-Wave) and very large multiple antenna systems (VLMAS) are two key technologies in the deployment of Fifth Generation (5G) mobile communication systems. In order to exploit all the benefits of VLMAS, spatial and temporal (ST) features must be estimated and exploited to compute the precoding/decoding matrices. In the literature, a practical channel estimation approach is proposed by assuming that the spatial features are completely unknown, leading to non-parametric estimation in which antenna array calibration is not required. Additionally, when the signal-to-noise ratio (SNR) is not so high, a low-rank (LR) version of the estimated channel is proposed that provides better performance than the full-rank (FR) one in terms of bias-variance trade-off in the mean squared error (MSE). However, previous work assumes that spatial and temporal characteristics of the channel can be estimated separately. Then, the performance is degraded in realistic channels. In this paper, we propose an alternative way to characterize the FR estimated channel using a joint ST covariance matrix, combined with a low-complexity semi-parametric spatial response and delay estimation technique. Moreover, we propose an automatic rank-selector (ARS) based on the MSE in order to provide the best LR channel estimation for each scenario. Numerical results show that the proposed technique outperforms existing approaches in the literature.en
dc.description.sponsorshipThis work has been partly funded by projects TERESA-ADA (TEC2017-90093-C3-2-R)(MINECO/AEI/FEDER, UE) and the fellowship of University Carlos III of Madrid under the program "Ayudas para la Movilidad del Programa Propio de Investigacion" granted to K. Chen-Huen
dc.format.extent6
dc.identifier.bibliographicCitationChen-Hu, K., Slock, D. T. M. & Garcia Armada, A. (20-24 May 2019). Low-rank channel estimation for mm-Wave multiple antenna systems using joint spatio-temporal covariance matrix [proceedings]. 2019 IEEE International Conference on Communications Workshops (ICC Workshops), Shanghai, China.en
dc.identifier.doihttps://doi.org/10.1109/ICCW.2019.8757027
dc.identifier.isbn978-1-7281-2373-8
dc.identifier.publicationfirstpage1
dc.identifier.publicationlastpage6
dc.identifier.publicationtitle2019 IEEE International Conference on Communications Workshops (ICC Workshops)en
dc.identifier.urihttps://hdl.handle.net/10016/36634
dc.identifier.uxxiCC/0000030664
dc.language.isoeng
dc.publisherIEEE
dc.relation.eventdate2019-01-20
dc.relation.eventplaceChinaes
dc.relation.eventtitleIEEE International Conference on Communicationsen
dc.relation.ispartofhttp://hdl.handle.net/10016/29609
dc.relation.projectIDGobierno de España. TEC2017-90093-C3-2-Res
dc.rights© 2019, IEEE
dc.rights.accessRightsopen accessen
dc.subject.ecienciaTelecomunicacioneses
dc.subject.other5G mobile communicationen
dc.subject.otherChannel codingen
dc.subject.otherChannel estimationen
dc.subject.otherCovariance matricesen
dc.subject.otherDecodingen
dc.subject.otherMean square error methodsen
dc.subject.otherMillimetre wave antenna arraysen
dc.subject.otherPrecodinen
dc.subject.otherWireless channelsen
dc.titleLow-rank channel estimation for mm-Wave multiple antenna systems using joint spatio-temporal covariance matrixen
dc.typeconference proceedings*
dc.type.hasVersionAM*
dspace.entity.typePublication
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