Design of RIS-aided mMTC+ networks for rate maximization under the finite blocklength regime with imperfect channel knowledge

© 2025 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 se...

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Autores: Liesegang, Sergi, Pascual Iserte, Antonio|||0000-0001-5596-2029, Muñoz Medina, Olga|||0000-0002-8739-7068, Zappone, Alessio
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/447028
Acceso en línea:https://hdl.handle.net/2117/447028
https://dx.doi.org/10.1109/LCOMM.2025.3600591
Access Level:acceso abierto
Palabra clave:Interference
Signal to noise ratio
Channel estimation
Reconfigurable intelligent surfaces
Spatial filters
Reflection
Optimization
Lower bound
Finite element analysis
Convex functions
Finite blocklength regime
Non-convex problem
Reconfigurable intelligent surface
Channel estimation error
Degrees of freedom
Numerical methods
Data mining
Internet of things
Line-of-sight
Beamforming
Previous point
Spatial filter
Minimum mean square error
Channel capacity
Similar technologies
Signal-to-interference-plus-noise ratio
Perfect channel state information
Imperfect channel state information
Semidefinite relaxation
Artificial intelligence training
Maximum ratio combining
Reconfigurable intelligent surface elements
Citation information
Massive machine-type communications
Successive convex optimization
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
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spelling Design of RIS-aided mMTC+ networks for rate maximization under the finite blocklength regime with imperfect channel knowledgeLiesegang, SergiPascual Iserte, Antonio|||0000-0001-5596-2029Muñoz Medina, Olga|||0000-0002-8739-7068Zappone, AlessioInterferenceSignal to noise ratioChannel estimationReconfigurable intelligent surfacesSpatial filtersReflectionOptimizationLower boundFinite element analysisConvex functionsFinite blocklength regimeNon-convex problemReconfigurable intelligent surfaceChannel estimation errorDegrees of freedomNumerical methodsData miningInternet of thingsLine-of-sightBeamformingPrevious pointSpatial filterMinimum mean square errorChannel capacitySimilar technologiesSignal-to-interference-plus-noise ratioPerfect channel state informationImperfect channel state informationSemidefinite relaxationArtificial intelligence trainingMaximum ratio combiningReconfigurable intelligent surface elementsCitation informationMassive machine-type communicationsReconfigurable intelligent surfacesFinite blocklength regimeChannel estimationSuccessive convex optimizationÀrees temàtiques de la UPC::Enginyeria de la telecomunicació© 2025 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 other works.Within the context of massive machine-type communications+, reconfigurable intelligent surfaces (RISs) represent a promising technology to boost system performance in scenarios with poor channel conditions. Considering single-antenna sensors transmitting short data packets to a multiple-antenna collector node, we introduce and design an RIS to maximize the weighted sum rate (WSR) of the system working in the finite blocklength regime. Due to the large number of reflecting elements and their passive nature, channel estimation errors may occur. In this letter, we then propose a robust RIS optimization to combat such a detrimental issue. Based on concave bounds and approximations, the nonconvex WSR problem for the RIS response is addressed via successive convex optimization (SCO). Numerical experiments validate the performance and complexity of the SCO solutions.The work of S. Liesegang, A. Pascual-Iserte, and O. Munoz is part of the I+D+i project 6-SENSES (PID2022-138648OB-I00), funded by MI- CIU/AEI/10.13039/501100011033 and ERDF/EUPeer Reviewed20252025-11-0120252025-11-25journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/447028https://dx.doi.org/10.1109/LCOMM.2025.3600591reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengAgencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2022-138648OB-I00 COMUNICACIONES 6G Y SENSADO PARA REDES INALAMBRICAS DETERMINISTASopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4470282026-05-27T15:37:01Z
dc.title.none.fl_str_mv Design of RIS-aided mMTC+ networks for rate maximization under the finite blocklength regime with imperfect channel knowledge
title Design of RIS-aided mMTC+ networks for rate maximization under the finite blocklength regime with imperfect channel knowledge
spellingShingle Design of RIS-aided mMTC+ networks for rate maximization under the finite blocklength regime with imperfect channel knowledge
Liesegang, Sergi
Interference
Signal to noise ratio
Channel estimation
Reconfigurable intelligent surfaces
Spatial filters
Reflection
Optimization
Lower bound
Finite element analysis
Convex functions
Finite blocklength regime
Non-convex problem
Reconfigurable intelligent surface
Channel estimation error
Degrees of freedom
Numerical methods
Data mining
Internet of things
Line-of-sight
Beamforming
Previous point
Spatial filter
Minimum mean square error
Channel capacity
Similar technologies
Signal-to-interference-plus-noise ratio
Perfect channel state information
Imperfect channel state information
Semidefinite relaxation
Artificial intelligence training
Maximum ratio combining
Reconfigurable intelligent surface elements
Citation information
Massive machine-type communications
Reconfigurable intelligent surfaces
Finite blocklength regime
Channel estimation
Successive convex optimization
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
title_short Design of RIS-aided mMTC+ networks for rate maximization under the finite blocklength regime with imperfect channel knowledge
title_full Design of RIS-aided mMTC+ networks for rate maximization under the finite blocklength regime with imperfect channel knowledge
title_fullStr Design of RIS-aided mMTC+ networks for rate maximization under the finite blocklength regime with imperfect channel knowledge
title_full_unstemmed Design of RIS-aided mMTC+ networks for rate maximization under the finite blocklength regime with imperfect channel knowledge
title_sort Design of RIS-aided mMTC+ networks for rate maximization under the finite blocklength regime with imperfect channel knowledge
dc.creator.none.fl_str_mv Liesegang, Sergi
Pascual Iserte, Antonio|||0000-0001-5596-2029
Muñoz Medina, Olga|||0000-0002-8739-7068
Zappone, Alessio
author Liesegang, Sergi
author_facet Liesegang, Sergi
Pascual Iserte, Antonio|||0000-0001-5596-2029
Muñoz Medina, Olga|||0000-0002-8739-7068
Zappone, Alessio
author_role author
author2 Pascual Iserte, Antonio|||0000-0001-5596-2029
Muñoz Medina, Olga|||0000-0002-8739-7068
Zappone, Alessio
author2_role author
author
author
dc.subject.none.fl_str_mv Interference
Signal to noise ratio
Channel estimation
Reconfigurable intelligent surfaces
Spatial filters
Reflection
Optimization
Lower bound
Finite element analysis
Convex functions
Finite blocklength regime
Non-convex problem
Reconfigurable intelligent surface
Channel estimation error
Degrees of freedom
Numerical methods
Data mining
Internet of things
Line-of-sight
Beamforming
Previous point
Spatial filter
Minimum mean square error
Channel capacity
Similar technologies
Signal-to-interference-plus-noise ratio
Perfect channel state information
Imperfect channel state information
Semidefinite relaxation
Artificial intelligence training
Maximum ratio combining
Reconfigurable intelligent surface elements
Citation information
Massive machine-type communications
Reconfigurable intelligent surfaces
Finite blocklength regime
Channel estimation
Successive convex optimization
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
topic Interference
Signal to noise ratio
Channel estimation
Reconfigurable intelligent surfaces
Spatial filters
Reflection
Optimization
Lower bound
Finite element analysis
Convex functions
Finite blocklength regime
Non-convex problem
Reconfigurable intelligent surface
Channel estimation error
Degrees of freedom
Numerical methods
Data mining
Internet of things
Line-of-sight
Beamforming
Previous point
Spatial filter
Minimum mean square error
Channel capacity
Similar technologies
Signal-to-interference-plus-noise ratio
Perfect channel state information
Imperfect channel state information
Semidefinite relaxation
Artificial intelligence training
Maximum ratio combining
Reconfigurable intelligent surface elements
Citation information
Massive machine-type communications
Reconfigurable intelligent surfaces
Finite blocklength regime
Channel estimation
Successive convex optimization
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
description © 2025 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 other works.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-11-01
2025
2025-11-25
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/447028
https://dx.doi.org/10.1109/LCOMM.2025.3600591
url https://hdl.handle.net/2117/447028
https://dx.doi.org/10.1109/LCOMM.2025.3600591
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2022-138648OB-I00 COMUNICACIONES 6G Y SENSADO PARA REDES INALAMBRICAS DETERMINISTAS
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812455

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