Super-resolution for doubly-dispersive channel estimation

dc.contributor.authorBeinert, Robert
dc.contributor.authorJung, Peter
dc.contributor.authorSteidl, Gabriele
dc.contributor.authorSzollmann, Tom
dc.date.accessioned2021-12-13T07:23:04Z
dc.date.available2021-12-13T07:23:04Z
dc.date.issued2021-10-13
dc.description.abstractIn this work we consider the problem of identification and reconstruction of doubly-dispersive channel operators which are given by finite linear combinations of time-frequency shifts. Such operators arise as time-varying linear systems for example in radar and wireless communications. In particular, for information transmission in highly non-stationary environments the channel needs to be estimated quickly with identification signals of short duration and for vehicular application simultaneous high-resolution radar is desired as well. We consider the time-continuous setting and prove an exact resampling reformulation of the involved channel operator when applied to a trigonometric polynomial as identifier in terms of sparse linear combinations of real-valued atoms. Motivated by recent works of Heckel et al. we present an exact approach for off-the-grid super-resolution which allows to perform the identification with realizable signals having compact support. Then we show how an alternating descent conditional gradient algorithm can be adapted to solve the reformulated problem. Numerical examples demonstrate the performance of this algorithm, in particular in comparison with a simple adaptive grid refinement strategy and an orthogonal matching pursuit algorithm.en
dc.description.sponsorshipTU Berlin, Open-Access-Mittel – 2021en
dc.identifier.eissn2730-5724
dc.identifier.issn2730-5716
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/14035
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-12808
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc510 Mathematikde
dc.subject.otherchannel estimationen
dc.subject.otherdoubly-dispersiveen
dc.subject.othersamplingen
dc.subject.othersuper-resolutionen
dc.subject.othertime-frequencyen
dc.titleSuper-resolution for doubly-dispersive channel estimationen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumber16en
dcterms.bibliographicCitation.doi10.1007/s43670-021-00016-0en
dcterms.bibliographicCitation.issue2en
dcterms.bibliographicCitation.journaltitleSampling Theory, Signal Processing, and Data Analysisen
dcterms.bibliographicCitation.originalpublishernameSpringer Natureen
dcterms.bibliographicCitation.originalpublisherplaceChamen
dcterms.bibliographicCitation.volume19en
tub.accessrights.dnbfreeen
tub.affiliationFak. 2 Mathematik und Naturwissenschaften::Inst. Mathematik::FG Angewandte Mathematikde
tub.affiliation.facultyFak. 2 Mathematik und Naturwissenschaften
tub.affiliation.groupFG Angewandte Mathematik
tub.affiliation.instituteInst. Mathematik
tub.publisher.universityorinstitutionTechnische Universität Berlinen

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