Simultaneous correlation of complementary set of sequences using a transpose generation approach

Autores
Funes, Marcos Alan; Donato, Patricio Gabriel; Hadad, Matías Nicolás; Carrica, Daniel Oscar; Benedetti, Mario
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Complementary sets of sequences are currently being applied to signal coding, radar, and multi-user systems, among others. Their particular mathematical properties make them adequate for multi-emission and noisy environments. Nowadays sustained efforts are being devoted to reduce the calculations involved in the generation and/or correlation of these signals by means of recursive algorithms. Some authors have proposed efficient algorithms that are based on modular architectures made up of adders, multipliers and delays. This work introduces a new approach to correlation algorithms of complementary sets of sequences, which is based on a transposition of the generation process. This approach allows to notoriously reduce calculations, and enables the simultaneous correlation of M sequences, without adopting time multiplexing schemes or complex parallel implementations. The correlation algorithm is theoretically demonstrated and its calculation performance is evaluated in a hardware reconfigurable platform. A comparison with other algorithms is included, considering the amount of calculations as a function of the length of the sequences.
Fil: Funes, Marcos Alan. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Donato, Patricio Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata; Argentina
Fil: Hadad, Matías Nicolás. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Carrica, Daniel Oscar. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Benedetti, Mario. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
Complementary set of sequences
Correlation
Efficient architecture
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/96087
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Simultaneous correlation of complementary set of sequences using a transpose generation approachFunes, Marcos AlanDonato, Patricio GabrielHadad, Matías NicolásCarrica, Daniel OscarBenedetti, MarioComplementary set of sequencesCorrelationEfficient architecturehttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Complementary sets of sequences are currently being applied to signal coding, radar, and multi-user systems, among others. Their particular mathematical properties make them adequate for multi-emission and noisy environments. Nowadays sustained efforts are being devoted to reduce the calculations involved in the generation and/or correlation of these signals by means of recursive algorithms. Some authors have proposed efficient algorithms that are based on modular architectures made up of adders, multipliers and delays. This work introduces a new approach to correlation algorithms of complementary sets of sequences, which is based on a transposition of the generation process. This approach allows to notoriously reduce calculations, and enables the simultaneous correlation of M sequences, without adopting time multiplexing schemes or complex parallel implementations. The correlation algorithm is theoretically demonstrated and its calculation performance is evaluated in a hardware reconfigurable platform. A comparison with other algorithms is included, considering the amount of calculations as a function of the length of the sequences.Fil: Funes, Marcos Alan. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Donato, Patricio Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata; ArgentinaFil: Hadad, Matías Nicolás. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Carrica, Daniel Oscar. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Benedetti, Mario. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaAcademic Press Inc Elsevier Science2013-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/96087Funes, Marcos Alan; Donato, Patricio Gabriel; Hadad, Matías Nicolás; Carrica, Daniel Oscar; Benedetti, Mario; Simultaneous correlation of complementary set of sequences using a transpose generation approach; Academic Press Inc Elsevier Science; Digital Signal Processing; 23; 3; 5-2013; 1044-10501051-2004CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1051200412002771info:eu-repo/semantics/altIdentifier/doi/10.1016/j.dsp.2012.11.008info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:50:56Zoai:ri.conicet.gov.ar:11336/96087instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:50:56.731CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Simultaneous correlation of complementary set of sequences using a transpose generation approach
title Simultaneous correlation of complementary set of sequences using a transpose generation approach
spellingShingle Simultaneous correlation of complementary set of sequences using a transpose generation approach
Funes, Marcos Alan
Complementary set of sequences
Correlation
Efficient architecture
title_short Simultaneous correlation of complementary set of sequences using a transpose generation approach
title_full Simultaneous correlation of complementary set of sequences using a transpose generation approach
title_fullStr Simultaneous correlation of complementary set of sequences using a transpose generation approach
title_full_unstemmed Simultaneous correlation of complementary set of sequences using a transpose generation approach
title_sort Simultaneous correlation of complementary set of sequences using a transpose generation approach
dc.creator.none.fl_str_mv Funes, Marcos Alan
Donato, Patricio Gabriel
Hadad, Matías Nicolás
Carrica, Daniel Oscar
Benedetti, Mario
author Funes, Marcos Alan
author_facet Funes, Marcos Alan
Donato, Patricio Gabriel
Hadad, Matías Nicolás
Carrica, Daniel Oscar
Benedetti, Mario
author_role author
author2 Donato, Patricio Gabriel
Hadad, Matías Nicolás
Carrica, Daniel Oscar
Benedetti, Mario
author2_role author
author
author
author
dc.subject.none.fl_str_mv Complementary set of sequences
Correlation
Efficient architecture
topic Complementary set of sequences
Correlation
Efficient architecture
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Complementary sets of sequences are currently being applied to signal coding, radar, and multi-user systems, among others. Their particular mathematical properties make them adequate for multi-emission and noisy environments. Nowadays sustained efforts are being devoted to reduce the calculations involved in the generation and/or correlation of these signals by means of recursive algorithms. Some authors have proposed efficient algorithms that are based on modular architectures made up of adders, multipliers and delays. This work introduces a new approach to correlation algorithms of complementary sets of sequences, which is based on a transposition of the generation process. This approach allows to notoriously reduce calculations, and enables the simultaneous correlation of M sequences, without adopting time multiplexing schemes or complex parallel implementations. The correlation algorithm is theoretically demonstrated and its calculation performance is evaluated in a hardware reconfigurable platform. A comparison with other algorithms is included, considering the amount of calculations as a function of the length of the sequences.
Fil: Funes, Marcos Alan. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Donato, Patricio Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata; Argentina
Fil: Hadad, Matías Nicolás. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Carrica, Daniel Oscar. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Benedetti, Mario. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Complementary sets of sequences are currently being applied to signal coding, radar, and multi-user systems, among others. Their particular mathematical properties make them adequate for multi-emission and noisy environments. Nowadays sustained efforts are being devoted to reduce the calculations involved in the generation and/or correlation of these signals by means of recursive algorithms. Some authors have proposed efficient algorithms that are based on modular architectures made up of adders, multipliers and delays. This work introduces a new approach to correlation algorithms of complementary sets of sequences, which is based on a transposition of the generation process. This approach allows to notoriously reduce calculations, and enables the simultaneous correlation of M sequences, without adopting time multiplexing schemes or complex parallel implementations. The correlation algorithm is theoretically demonstrated and its calculation performance is evaluated in a hardware reconfigurable platform. A comparison with other algorithms is included, considering the amount of calculations as a function of the length of the sequences.
publishDate 2013
dc.date.none.fl_str_mv 2013-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/96087
Funes, Marcos Alan; Donato, Patricio Gabriel; Hadad, Matías Nicolás; Carrica, Daniel Oscar; Benedetti, Mario; Simultaneous correlation of complementary set of sequences using a transpose generation approach; Academic Press Inc Elsevier Science; Digital Signal Processing; 23; 3; 5-2013; 1044-1050
1051-2004
CONICET Digital
CONICET
url http://hdl.handle.net/11336/96087
identifier_str_mv Funes, Marcos Alan; Donato, Patricio Gabriel; Hadad, Matías Nicolás; Carrica, Daniel Oscar; Benedetti, Mario; Simultaneous correlation of complementary set of sequences using a transpose generation approach; Academic Press Inc Elsevier Science; Digital Signal Processing; 23; 3; 5-2013; 1044-1050
1051-2004
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1051200412002771
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.dsp.2012.11.008
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Academic Press Inc Elsevier Science
publisher.none.fl_str_mv Academic Press Inc Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.982451

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