Robust channel estimation for ultra-wide band communications

UWB (ultra-wide band) systems transmit low power signals through communication channels that operate in closed environments and in short distances resulting in multiple propagation trajectories. Moreover, the noise affecting these channels can be characterized by the use of statistical models with h...

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Autores:: Yánez Sánchez, Nicey Alberto
Ramirez, Juan Marcos
Paredes, Jose Luis
Pinto, Angel Dario
Torres, Jose Manuel
Perez, Marvin Luis

Tipo de recurso:: Article of journal

Fecha de publicación:: 2019

Institución:: Universidad de Medellín

Repositorio:: Repositorio UDEM

Idioma:: spa

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network_acronym_str	REPOUDEM2
network_name_str	Repositorio UDEM
repository_id_str
dc.title.eng.fl_str_mv	Robust channel estimation for ultra-wide band communications
dc.title.por.fl_str_mv	Estimativa robusta de canais de comunicação de ultrabanda larga
dc.title.spa.fl_str_mv	Estimación robusta de canales de comunicaciones de ultra banda ancha
title	Robust channel estimation for ultra-wide band communications
spellingShingle	Robust channel estimation for ultra-wide band communications Ultra wide-band Weighted median Channel model Low density representation Robust channel estimation Ultra wide-band Média ponderada Modelo do canal Representação pouco poco densa Estimativa robusta do canal Ultra wide-band Mediana ponderada Modelo del canal Representación poco densa Estimación robusta del canal
title_short	Robust channel estimation for ultra-wide band communications
title_full	Robust channel estimation for ultra-wide band communications
title_fullStr	Robust channel estimation for ultra-wide band communications
title_full_unstemmed	Robust channel estimation for ultra-wide band communications
title_sort	Robust channel estimation for ultra-wide band communications
dc.creator.fl_str_mv	Yánez Sánchez, Nicey Alberto Ramirez, Juan Marcos Paredes, Jose Luis Pinto, Angel Dario Torres, Jose Manuel Perez, Marvin Luis
dc.contributor.author.none.fl_str_mv	Yánez Sánchez, Nicey Alberto Ramirez, Juan Marcos Paredes, Jose Luis Pinto, Angel Dario Torres, Jose Manuel Perez, Marvin Luis
dc.subject.eng.fl_str_mv	Ultra wide-band Weighted median Channel model Low density representation Robust channel estimation
topic	Ultra wide-band Weighted median Channel model Low density representation Robust channel estimation Ultra wide-band Média ponderada Modelo do canal Representação pouco poco densa Estimativa robusta do canal Ultra wide-band Mediana ponderada Modelo del canal Representación poco densa Estimación robusta del canal
dc.subject.por.fl_str_mv	Ultra wide-band Média ponderada Modelo do canal Representação pouco poco densa Estimativa robusta do canal
dc.subject.spa.fl_str_mv	Ultra wide-band Mediana ponderada Modelo del canal Representación poco densa Estimación robusta del canal
description	UWB (ultra-wide band) systems transmit low power signals through communication channels that operate in closed environments and in short distances resulting in multiple propagation trajectories. Moreover, the noise affecting these channels can be characterized by the use of statistical models with heavier tails that the ones exhibited by gaussian distribution. This article proposes a robust approach for the estimation of the parameters of UWB channels based on the weighted median. More specifically, it develops an algorithm of greedy search that exploits the low density characteristic of the channel’s impulsive response, in which the gains and delays of the relevant channels are determined by applying the weighted median on an scaled and displaced version of the signal received. This newly introduced algorithm is evaluated using extensive simulations in which the performance of the proposed algorithm surpasses the performance of the traditional greedy search algorithm for different levels of impulsive noise.
publishDate	2019
dc.date.accessioned.none.fl_str_mv	2019-11-07T15:34:27Z
dc.date.available.none.fl_str_mv	2019-11-07T15:34:27Z
dc.date.created.none.fl_str_mv	2019-06-28
dc.type.eng.fl_str_mv	Article
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dc.type.local.spa.fl_str_mv	Artículo científico
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dc.identifier.issn.none.fl_str_mv	1692-3324
dc.identifier.uri.none.fl_str_mv	http://hdl.handle.net/11407/5526
dc.identifier.doi.none.fl_str_mv	https://doi.org/10.22395/rium.v18n34a11
dc.identifier.eissn.none.fl_str_mv	2248-4094
dc.identifier.reponame.spa.fl_str_mv	reponame:Repositorio Institucional Universidad de Medellín
dc.identifier.repourl.none.fl_str_mv	repourl:https://repository.udem.edu.co/
dc.identifier.instname.spa.fl_str_mv	instname:Universidad de Medellín
identifier_str_mv	1692-3324 2248-4094 reponame:Repositorio Institucional Universidad de Medellín repourl:https://repository.udem.edu.co/ instname:Universidad de Medellín
url	http://hdl.handle.net/11407/5526 https://doi.org/10.22395/rium.v18n34a11
dc.language.iso.none.fl_str_mv	spa
language	spa
dc.relation.uri.none.fl_str_mv	https://revistas.udem.edu.co/index.php/ingenierias/article/view/2228
dc.relation.citationvolume.none.fl_str_mv	18
dc.relation.citationissue.none.fl_str_mv	34
dc.relation.citationstartpage.none.fl_str_mv	181
dc.relation.citationendpage.none.fl_str_mv	197
dc.relation.references.spa.fl_str_mv	[1] K. Siwiak, Ultra‐Wideband Radio, Nueva York: John Wiley and Sons, 2004. [2] A. Ritcher, et al., “Maximum likelihood channel parameter estimation from multidimensional channel sounding measurements,” presentado en 2003 IEEE Vehicular Technology Conference, Orlando, 2003. [3] S.F. Cotter y B.D. Rao, “Sparse channel estimation via matching pursuit with application to equalization,” IEEE Transactions on Communications, vol. 50, n.° 3, pp. 374-377, 2002. [4] M. Sharp y A. Scaglione, A., “Estimation of sparse multipath channels,” presentado en Military Communications Conference, San Diego, 2008. [5] J. Paredes et al., “Ultra-wideband compressed sensing: Channel estimation,” IEEE Journal of Selected Topics in Signal Processing, vol. 1, n.° 3, pp. 383-395, 2007. [6] H. El Ghannudi et al., “α-stable interference modeling and Cauchy receiver for an IR-UWB ad hoc network,” IEEE Transactions on Communications, vol. 58, n.° 6, pp. 1748-1757, 2010. [7] RC Qiu et al., (2005). “Ultra-wideband for multiple access communications,” IEEE Communications Magazine, vol. 43, n.° 2, pp. 80-87, 2005. [8] H. Arslan et al., Ultra wideband wireless communication, Nueva York: John Wiley and Sons, 2006. [9] TK Liu et al., “Compressed sensing maximum likelihood channel estimation for ultrawideband impulse radio,” presentado en IEEE International Conference on Communications, Dresden, 2009. [10] FM Naini et al., “Compressive sampling of pulse trains: Spread the Spectrum,” presentado en IEEE International Conference on Acoustics, Speech and Signal Processing, Taipei, 2009. [11] V. Lottici et al., “Channel estimation for ultra-wideband communications,” IEEE Journal on selected areas in communications, vol. 20, n.° 9, pp. 1638-1645, 2002. [12] G. Gui et al., “Sparse multipath channel estimation using compressive sampling matching pursuit algorithm,” presentado en IEEE Vehicular Technology Socety Asia Pacific Wireless Communications Simposium, Taiwan, 2010. 13] B. S. Kim et al., “A comparative analysis of optimum and suboptimum rake receivers in impulsive UWB environment” IEEE Transactions on Vehicular Technology, vol. 55, n.° 6, pp. 1797-1804, 2006. [14] H. Hashemi, “The indoor radio propagation channel” IEEE Journal on Selected Areas in Communications, vol. 11, n.° 7, pp. 943-968, 1993. [15] J. Paredes y G. Arce, “Compressive sensing signal reconstruction by weighted median regression estimates” IEEE Transactions on Signal Processing, vol. 59, n.° 6, pp. 2585-2601, 2011. [16] J. Foerster, Ed., “Channel modeling sub-committee report final,” IEEE P802. 15 Working Group for Wireless Personal Area Networks (WPANs), IEEE P802. 15-02/490r1-SG3a, 2003. [17] J. Gonzalez et al., “Zero-order statistics: a mathematical framework for the processing and characterization of very impulsive signals,” IEEE Transactions on Signal Processing, vol. 54, n.° 10, pp. 3839-3851, 2006.
dc.relation.ispartofjournal.spa.fl_str_mv	Revista Ingenierías Universidad de Medellín
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dc.rights.uri.*.fl_str_mv	http://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rights.creativecommons.*.fl_str_mv	Attribution-NonCommercial-ShareAlike 4.0 International
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dc.format.extent.spa.fl_str_mv	p. 181-197
dc.format.medium.spa.fl_str_mv	Electrónico
dc.format.mimetype.none.fl_str_mv	application/pdf
dc.coverage.none.fl_str_mv	Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degreesLong: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees
dc.publisher.spa.fl_str_mv	Universidad de Medellín
dc.publisher.faculty.spa.fl_str_mv	Facultad de Ingenierías
dc.publisher.place.spa.fl_str_mv	Medellín
dc.source.spa.fl_str_mv	Revista Ingenierías Universidad de Medellín; Vol. 18 Núm. 34 (2019): Enero-Junio; 181-197
institution	Universidad de Medellín
repository.name.fl_str_mv	Repositorio Institucional Universidad de Medellin
repository.mail.fl_str_mv	repositorio@udem.edu.co
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spelling	Yánez Sánchez, Nicey AlbertoRamirez, Juan MarcosParedes, Jose LuisPinto, Angel DarioTorres, Jose ManuelPerez, Marvin LuisYánez Sánchez, Nicey Alberto; Paperless LatinoaméricaRamirez, Juan Marcos; Universidad de Los Andes, Merida, VenezuelaParedes, Jose Luis; Universidad de Los Andes, Merida, VenezuelaPinto, Angel Dario; Universidad del Sinú, ColombiaTorres, Jose Manuel; Universidad del Sinú, ColombiaPerez, Marvin Luis; Universidad Cooperativa de Colombia2019-11-07T15:34:27Z2019-11-07T15:34:27Z2019-06-281692-3324http://hdl.handle.net/11407/5526https://doi.org/10.22395/rium.v18n34a112248-4094reponame:Repositorio Institucional Universidad de Medellínrepourl:https://repository.udem.edu.co/instname:Universidad de MedellínUWB (ultra-wide band) systems transmit low power signals through communication channels that operate in closed environments and in short distances resulting in multiple propagation trajectories. Moreover, the noise affecting these channels can be characterized by the use of statistical models with heavier tails that the ones exhibited by gaussian distribution. This article proposes a robust approach for the estimation of the parameters of UWB channels based on the weighted median. More specifically, it develops an algorithm of greedy search that exploits the low density characteristic of the channel’s impulsive response, in which the gains and delays of the relevant channels are determined by applying the weighted median on an scaled and displaced version of the signal received. This newly introduced algorithm is evaluated using extensive simulations in which the performance of the proposed algorithm surpasses the performance of the traditional greedy search algorithm for different levels of impulsive noise.Os sistemas UWB (ultra-wide band) transmitem sinais a baixa potência por meio de canais de comunicação que operam em ambientes fechados e em distâncias curtas, o que origina múltiplas trajetórias de propagação. Além disso, o ruído que afeta esses canais pode ser caracterizado mediante o uso de modelos estatísticos de caudas mais pesadas que as exibidas pela distribuição gaussiana. Neste artigo, propõe-se uma abordagem robusta para estimar os parâmetros dos canais UWB baseado na média ponderada. Em específico, desenvolve-se um algoritmo de busca voraz que aproveita a característica pouco densa da resposta impulsiva do canal, em que os ganhos e os atrasos dos canais relevantes são determinados aplicando a média ponderada sobre uma versão escalada e deslocada do sinal recebido. O algoritmo proposto é avaliado usando extensas simulações nas quais o rendimento do algoritmo proposto supera o desempenho do algoritmo de busca voraz tradicional para diferentes níveis de ruído impulsivo.Los sistemas UWB (ultra-wide band) transmiten señales a baja potencia a través de canales de comunicaciones que operan en entornos cerrados y en distancias cortas, lo que origina múltiples trayectorias de propagación. Además, el ruido que afecta a estos canales se puede caracterizar mediante el uso de modelos estadísticos de colas más pesadas que las exhibidas por la distribución gaussiana. En este artículo, se propone un enfoque robusto para la estimación de los parámetros de los canales UWB basado en la mediana ponderada. Específicamente, se desarrolla un algoritmo de búsqueda voraz que aprovecha la característica poco densa de la respuesta impulsiva del canal, donde las ganancias y los retardos de los canales relevantes se determinan aplicando la mediana ponderada sobre una versión escalada y desplazada de la señal recibida. El algoritmo propuesto se evalúa usando extensas simulaciones en las que el rendimiento del algoritmo propuesto supera el desempeño del algoritmo de búsqueda voraz tradicional para diferentes niveles de ruido impulsivo.p. 181-197Electrónicoapplication/pdfspaUniversidad de MedellínFacultad de IngenieríasMedellínhttps://revistas.udem.edu.co/index.php/ingenierias/article/view/22281834181197[1] K. Siwiak, Ultra‐Wideband Radio, Nueva York: John Wiley and Sons, 2004.[2] A. Ritcher, et al., “Maximum likelihood channel parameter estimation from multidimensional channel sounding measurements,” presentado en 2003 IEEE Vehicular Technology Conference, Orlando, 2003.[3] S.F. Cotter y B.D. Rao, “Sparse channel estimation via matching pursuit with application to equalization,” IEEE Transactions on Communications, vol. 50, n.° 3, pp. 374-377, 2002.[4] M. Sharp y A. Scaglione, A., “Estimation of sparse multipath channels,” presentado en Military Communications Conference, San Diego, 2008.[5] J. Paredes et al., “Ultra-wideband compressed sensing: Channel estimation,” IEEE Journal of Selected Topics in Signal Processing, vol. 1, n.° 3, pp. 383-395, 2007.[6] H. El Ghannudi et al., “α-stable interference modeling and Cauchy receiver for an IR-UWB ad hoc network,” IEEE Transactions on Communications, vol. 58, n.° 6, pp. 1748-1757, 2010.[7] RC Qiu et al., (2005). “Ultra-wideband for multiple access communications,” IEEE Communications Magazine, vol. 43, n.° 2, pp. 80-87, 2005.[8] H. Arslan et al., Ultra wideband wireless communication, Nueva York: John Wiley and Sons, 2006.[9] TK Liu et al., “Compressed sensing maximum likelihood channel estimation for ultrawideband impulse radio,” presentado en IEEE International Conference on Communications, Dresden, 2009.[10] FM Naini et al., “Compressive sampling of pulse trains: Spread the Spectrum,” presentado en IEEE International Conference on Acoustics, Speech and Signal Processing, Taipei, 2009.[11] V. Lottici et al., “Channel estimation for ultra-wideband communications,” IEEE Journal on selected areas in communications, vol. 20, n.° 9, pp. 1638-1645, 2002.[12] G. Gui et al., “Sparse multipath channel estimation using compressive sampling matching pursuit algorithm,” presentado en IEEE Vehicular Technology Socety Asia Pacific Wireless Communications Simposium, Taiwan, 2010.13] B. S. Kim et al., “A comparative analysis of optimum and suboptimum rake receivers in impulsive UWB environment” IEEE Transactions on Vehicular Technology, vol. 55, n.° 6, pp. 1797-1804, 2006.[14] H. Hashemi, “The indoor radio propagation channel” IEEE Journal on Selected Areas in Communications, vol. 11, n.° 7, pp. 943-968, 1993.[15] J. Paredes y G. Arce, “Compressive sensing signal reconstruction by weighted median regression estimates” IEEE Transactions on Signal Processing, vol. 59, n.° 6, pp. 2585-2601, 2011.[16] J. Foerster, Ed., “Channel modeling sub-committee report final,” IEEE P802. 15 Working Group for Wireless Personal Area Networks (WPANs), IEEE P802. 15-02/490r1-SG3a, 2003.[17] J. Gonzalez et al., “Zero-order statistics: a mathematical framework for the processing and characterization of very impulsive signals,” IEEE Transactions on Signal Processing, vol. 54, n.° 10, pp. 3839-3851, 2006.Revista Ingenierías Universidad de Medellínhttp://creativecommons.org/licenses/by-nc-sa/4.0/Attribution-NonCommercial-ShareAlike 4.0 Internationalhttp://purl.org/coar/access_right/c_abf2Revista Ingenierías Universidad de Medellín; Vol. 18 Núm. 34 (2019): Enero-Junio; 181-197Ultra wide-bandWeighted medianChannel modelLow density representationRobust channel estimationUltra wide-bandMédia ponderadaModelo do canalRepresentação pouco poco densaEstimativa robusta do canalUltra wide-bandMediana ponderadaModelo del canalRepresentación poco densaEstimación robusta del canalRobust channel estimation for ultra-wide band communicationsEstimativa robusta de canais de comunicação de ultrabanda largaEstimación robusta de canales de comunicaciones de ultra banda anchaArticlehttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Artículo científicoinfo:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a85Comunidad Universidad de MedellínLat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degreesLong: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees11407/5526oai:repository.udem.edu.co:11407/55262021-05-14 14:29:54.815Repositorio Institucional Universidad de Medellinrepositorio@udem.edu.co

Robust channel estimation for ultra-wide band communications

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