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dc.contributor.authorMolina-Masegosa, Rafael-
dc.contributor.authorSepulcre, Miguel-
dc.contributor.authorGozalvez, Javier-
dc.contributor.authorBerens, Friedbert-
dc.contributor.authorMartinez, Vincent-
dc.contributor.otherDepartamentos de la UMH::Ingeniería de Comunicacioneses_ES
dc.date.accessioned2024-02-02T09:57:27Z-
dc.date.available2024-02-02T09:57:27Z-
dc.date.created2020-05-
dc.identifier.citationIEEE Transactions on Vehicular Technology ( Volume: 69, Issue: 5, May 2020)es_ES
dc.identifier.issn1939-9359-
dc.identifier.issn0018-9545-
dc.identifier.urihttps://hdl.handle.net/11000/30966-
dc.description.abstractMost V2X (Vehicle-to-Everything) applications rely on broadcasting awareness messages known as CAM (Cooperative Awareness Messages) in ETSI or BSM (Basic Safety Message) in SAE standards. A large number of studies have been devoted to guarantee their reliable transmission. However, to date, the studies are generally based on simplified data traffic models that generate awareness messages at periodic intervals or with a constant message size. These models do not accurately represent the real generation of CAM messages that follow specific mobility-based rules. Using simplified and unrealistic traffic models can significantly impact the results and validity of the studies, and hence accurate models for the generation of awareness messages are necessary. This paper proposes the first set of models that can realistically generate CAM messages. The models have been created from real traces collected by two car manufacturers in urban, sub-urban and highway test drives. The models are based on mth order Markov sources, and model the size of CAMs and the time interval between CAMs. The models are openly provided to the community and can be easily integrated into any simulator.es_ES
dc.formatapplication/pdfes_ES
dc.format.extent5es_ES
dc.language.isoenges_ES
dc.publisherInstitute of Electrical and Electronics Engineerses_ES
dc.rightsinfo:eu-repo/semantics/closedAccesses_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectV2Xes_ES
dc.subjectvehicular networkses_ES
dc.subjectCAMes_ES
dc.subjectBSMes_ES
dc.subjectawarenesses_ES
dc.subject.classificationTeoría de la señal y comunicacioneses_ES
dc.subject.otherCDU::6 - Ciencias aplicadas::62 - Ingeniería. Tecnologíaes_ES
dc.titleEmpirical Models for the Realistic Generation of Cooperative Awareness Messages in Vehicular Networkses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.1109/TVT.2020.2979232es_ES
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