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dc.contributor.authorCuevas Fernández, Diego 
dc.contributor.authorÁlvarez Vizoso, Javier 
dc.contributor.authorBeltrán Álvarez, Carlos 
dc.contributor.authorSantamaría Caballero, Luis Ignacio 
dc.contributor.authorTucek, Vít
dc.contributor.authorPeters, Gunnar
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2023-06-01T08:00:19Z
dc.date.available2023-06-01T08:00:19Z
dc.date.issued2023-04
dc.identifier.issn0090-6778
dc.identifier.issn1558-0857
dc.identifier.otherPID2020-113887GB-I00es_ES
dc.identifier.otherPID2019-104958RB-C43es_ES
dc.identifier.urihttps://hdl.handle.net/10902/29182
dc.description.abstractIn this paper, we propose an algorithm for designing unstructured Grassmannian constellations for noncoherent multiple-input multiple-output (MIMO) communications over Rayleigh block-fading channels. Unlike the majority of existing unitary space-time or Grassmannian constellations, which are typically designed to maximize the minimum distance between codewords, in this work we employ the asymptotic pairwise error probability (PEP) union bound (UB) of the constellation as the design criterion. In addition, the proposed criterion allows the design of MIMO Grassmannian constellations specifically optimized for a given number of receiving antennas. A rigorous derivation of the gradient of the asymptotic UB on a Cartesian product of Grassmann manifolds, is the main technical ingredient of the proposed gradient descent algorithm. A simple modification of the proposed cost function, which weighs each pairwise error term in the UB according to the Hamming distance between the binary labels assigned to the respective codewords, allows us to jointly solve the constellation design and the bit labeling problem. Our simulation results show that the constellations designed with the proposed method outperform other structured and unstructured Grassmannian designs in terms of symbol error rate (SER) and bit error rate (BER), for a wide range of scenarios.es_ES
dc.description.sponsorshipThis work was supported by Huawei Technologies, Sweden under the project GRASSCOM. The work of D. Cuevas was also partly supported under grant FPU20/03563 funded by Ministerio de Universidades (MIU), Spain. The work of Carlos Beltr´an was also partly supported under grant PID2020-113887GB-I00 funded by MCIN/ AEI /10.13039/501100011033. The work of I. Santamaria was also partly supported under grant PID2019-104958RB-C43 (ADELE) funded by MCIN/ AEI /10.13039/501100011033.es_ES
dc.format.extent13 p.es_ES
dc.language.isoenges_ES
dc.publisherInstitute of Electrical and Electronics Engineers Inc.es_ES
dc.rights© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in otheres_ES
dc.sourceIEEE Transactions on Communications, 2023, 71(4), 1940 -1952es_ES
dc.subject.otherNoncoherent communicationses_ES
dc.subject.otherMIMO communicationses_ES
dc.subject.otherGrassmannian constellationses_ES
dc.subject.otherPairwise error probability (PEP)es_ES
dc.subject.otherUnion bound (UB)es_ES
dc.subject.otherBit-labelinges_ES
dc.titleUnion bound minimization approach for designing grassmannian constellationses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1109/TCOMM.2023.3244965es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1109/TCOMM.2023.3244965
dc.type.versionacceptedVersiones_ES


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