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An experimental assessment of channel selection in cognitive radio networks
dc.contributor.author | Umbert Juliana, Anna |
dc.contributor.author | Sallent Roig, Oriol |
dc.contributor.author | Pérez Romero, Jordi |
dc.contributor.author | Sánchez González, Juan |
dc.contributor.author | Collins, Diarmuid |
dc.contributor.author | Kist, Maicon |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2018-12-14T16:35:58Z |
dc.date.available | 2019-05-22T00:30:34Z |
dc.date.issued | 2018 |
dc.identifier.citation | Umbert, A., Sallent, J., Perez-Romero, J., Sanchez, J., Collins, D., Kist, M. An experimental assessment of channel selection in cognitive radio networks. A: International Conference on Artificial Intelligence Applications and Innovations. "Artificial Intelligence Applications and Innovations : AIAI 2018 IFIP WG 12.5 International Workshops, SEDSEAL, 5G-PINE, MHDW, and HEALTHIOT, Rhodes, Greece, May 25-27, 2018: proceedings". Berlín: Springer, 2018, p. 78-88. |
dc.identifier.isbn | 978-3-319-92016-0 |
dc.identifier.uri | http://hdl.handle.net/2117/125828 |
dc.description.abstract | The management of future networks is expected to fully exploit cognitive capabilities that embrace knowledge and intelligence, increasing the degree of automation, making the network more self-autonomous and enabling a personalized user experience. In this context, this paper presents the use of knowledge-based capabilities through a specific lab experiment focused on the Channel Selection functionality for Cognitive Radio Networks (CRN). The selection is based on a supervised classification that allows estimating the number of interfering sources existing in a given frequency channel. Four different classifiers are considered, namely decision tree, neural net-work, naive Bayes and Support Vector Machine (SVM). Additionally, a comparison against other channel selection strategies using Q-learning and game theory has also been performed. Results obtained in an illustrative and realistic test scenario have revealed that all the strategies allow identifying an optimum solution. However, the time to converge to this solution can be up to 27 times higher according to the algorithm selected. |
dc.format.extent | 11 p. |
dc.language.iso | eng |
dc.publisher | Springer |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Comunicacions mòbils |
dc.subject.lcsh | Cognitive radio networks |
dc.subject.lcsh | Mobile communication systems |
dc.subject.other | Channel selection |
dc.subject.other | Classification |
dc.subject.other | Cognitive radio |
dc.title | An experimental assessment of channel selection in cognitive radio networks |
dc.type | Conference report |
dc.subject.lemac | Ràdio cognitiva |
dc.subject.lemac | Comunicacions mòbils, Sistemes de |
dc.contributor.group | Universitat Politècnica de Catalunya. GRCM - Grup de Recerca en Comunicacions Mòbils |
dc.identifier.doi | 10.1007/978-3-319-92016-0_8 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | https://link.springer.com/chapter/10.1007/978-3-319-92016-0_8 |
dc.rights.access | Open Access |
local.identifier.drac | 23547631 |
dc.description.version | Postprint (author's final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/MINECO//TEC2013-41698-R/ES/REDES MOVILES EFICIENTES PARA LA AMPLIACION DE SERVICIOS A NUEVOS SECTORES PROFESIONALES/ |
dc.relation.projectid | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TEC2017-82651-R/ES/SOFTWARIZACION Y OPTIMIZACION AUTOMATICA DE REDES DE ACCESO RADIO 5G MULTI-TENANT/ |
local.citation.author | Umbert, A.; Sallent, J.; Perez-Romero, J.; Sanchez, J.; Collins, D.; Kist, M. |
local.citation.contributor | International Conference on Artificial Intelligence Applications and Innovations |
local.citation.pubplace | Berlín |
local.citation.publicationName | Artificial Intelligence Applications and Innovations : AIAI 2018 IFIP WG 12.5 International Workshops, SEDSEAL, 5G-PINE, MHDW, and HEALTHIOT, Rhodes, Greece, May 25-27, 2018: proceedings |
local.citation.startingPage | 78 |
local.citation.endingPage | 88 |