Estimating the medium access probability in large cognitive radio networks
Resumen:
During the last decade we have seen an explosive development of wireless technologies. Consequently the demand for electromagnetic spectrum has been growing dramatically resulting in the spectrum scarcity problem. In spite of this, spectrum utilization measurements have shown that licensed bands are vastly underutilized while unlicensed bands are too crowded. In this context, Cognitive Radio Network emerges as an auspicious paradigm in order to solve those problems. The main question that motivates this work is: what are the possibilities offered by cognitive radio to improve the effectiveness of spectrum utilization? With this in mind, we propose a methodology, based on configuration models for random graphs, to estimate the medium access probability of secondary users. We perform simulations to illustrate the accuracy of our results and we also make a performance comparison between our estimation and one obtained by a stochastic geometry approach. Keywords : Cognitive radio networks, Random graphs, Stochastic geometry, Dynamic spectrum allocation, Fluid limit
| 2017 | |
|
Cognitive radio networks Random graphs Stochastic geometry Dynamic spectrum allocation Fluid limit Telecomunicaciones |
|
| Inglés | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/43525 | |
| Acceso abierto | |
| Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| _version_ | 1807522942178820096 |
|---|---|
| author | Rattaro, Claudina |
| author2 | Larroca, Federico Bermolen, Paola Belzarena, Pablo |
| author2_role | author author author |
| author_facet | Rattaro, Claudina Larroca, Federico Bermolen, Paola Belzarena, Pablo |
| author_role | author |
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| collection | COLIBRI |
| dc.creator.none.fl_str_mv | Rattaro, Claudina Larroca, Federico Bermolen, Paola Belzarena, Pablo |
| dc.date.accessioned.none.fl_str_mv | 2024-04-16T16:21:12Z |
| dc.date.available.none.fl_str_mv | 2024-04-16T16:21:12Z |
| dc.date.issued.es.fl_str_mv | 2017 |
| dc.date.submitted.es.fl_str_mv | 20240416 |
| dc.description.abstract.none.fl_txt_mv | During the last decade we have seen an explosive development of wireless technologies. Consequently the demand for electromagnetic spectrum has been growing dramatically resulting in the spectrum scarcity problem. In spite of this, spectrum utilization measurements have shown that licensed bands are vastly underutilized while unlicensed bands are too crowded. In this context, Cognitive Radio Network emerges as an auspicious paradigm in order to solve those problems. The main question that motivates this work is: what are the possibilities offered by cognitive radio to improve the effectiveness of spectrum utilization? With this in mind, we propose a methodology, based on configuration models for random graphs, to estimate the medium access probability of secondary users. We perform simulations to illustrate the accuracy of our results and we also make a performance comparison between our estimation and one obtained by a stochastic geometry approach. Keywords : Cognitive radio networks, Random graphs, Stochastic geometry, Dynamic spectrum allocation, Fluid limit |
| dc.identifier.citation.es.fl_str_mv | Rattaro, C, Larroca, F, Bermolen, P, Belzarena, P. "Estimating the medium access probability in large cognitive radio networks" Ad Hoc Networks, v. 63, 2017, pp: 1-13, https://doi.org/10.1016/j.adhoc.2017.05.003. |
| dc.identifier.uri.none.fl_str_mv | https://hdl.handle.net/20.500.12008/43525 |
| dc.language.iso.none.fl_str_mv | en eng |
| dc.rights.license.none.fl_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
| dc.subject.es.fl_str_mv | Cognitive radio networks Random graphs Stochastic geometry Dynamic spectrum allocation Fluid limit |
| dc.subject.other.es.fl_str_mv | Telecomunicaciones |
| dc.title.none.fl_str_mv | Estimating the medium access probability in large cognitive radio networks |
| dc.type.es.fl_str_mv | Preprint |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/preprint |
| dc.type.version.none.fl_str_mv | info:eu-repo/semantics/submittedVersion |
| description | During the last decade we have seen an explosive development of wireless technologies. Consequently the demand for electromagnetic spectrum has been growing dramatically resulting in the spectrum scarcity problem. In spite of this, spectrum utilization measurements have shown that licensed bands are vastly underutilized while unlicensed bands are too crowded. In this context, Cognitive Radio Network emerges as an auspicious paradigm in order to solve those problems. The main question that motivates this work is: what are the possibilities offered by cognitive radio to improve the effectiveness of spectrum utilization? With this in mind, we propose a methodology, based on configuration models for random graphs, to estimate the medium access probability of secondary users. We perform simulations to illustrate the accuracy of our results and we also make a performance comparison between our estimation and one obtained by a stochastic geometry approach. Keywords : Cognitive radio networks, Random graphs, Stochastic geometry, Dynamic spectrum allocation, Fluid limit |
| eu_rights_str_mv | openAccess |
| format | preprint |
| id | COLIBRI_6cd95bbf677b72412ccc3897edf5d55d |
| identifier_str_mv | Rattaro, C, Larroca, F, Bermolen, P, Belzarena, P. "Estimating the medium access probability in large cognitive radio networks" Ad Hoc Networks, v. 63, 2017, pp: 1-13, https://doi.org/10.1016/j.adhoc.2017.05.003. |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | COLIBRI |
| network_name_str | COLIBRI |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/43525 |
| publishDate | 2017 |
| reponame_str | COLIBRI |
| repository.mail.fl_str_mv | mabel.seroubian@seciu.edu.uy |
| repository.name.fl_str_mv | COLIBRI - Universidad de la República |
| repository_id_str | 4771 |
| rights_invalid_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| spelling | 2024-04-16T16:21:12Z2024-04-16T16:21:12Z201720240416Rattaro, C, Larroca, F, Bermolen, P, Belzarena, P. "Estimating the medium access probability in large cognitive radio networks" Ad Hoc Networks, v. 63, 2017, pp: 1-13, https://doi.org/10.1016/j.adhoc.2017.05.003.https://hdl.handle.net/20.500.12008/43525During the last decade we have seen an explosive development of wireless technologies. Consequently the demand for electromagnetic spectrum has been growing dramatically resulting in the spectrum scarcity problem. In spite of this, spectrum utilization measurements have shown that licensed bands are vastly underutilized while unlicensed bands are too crowded. In this context, Cognitive Radio Network emerges as an auspicious paradigm in order to solve those problems. The main question that motivates this work is: what are the possibilities offered by cognitive radio to improve the effectiveness of spectrum utilization? With this in mind, we propose a methodology, based on configuration models for random graphs, to estimate the medium access probability of secondary users. We perform simulations to illustrate the accuracy of our results and we also make a performance comparison between our estimation and one obtained by a stochastic geometry approach. Keywords : Cognitive radio networks, Random graphs, Stochastic geometry, Dynamic spectrum allocation, Fluid limitMade available in DSpace on 2024-04-16T16:21:12Z (GMT). No. of bitstreams: 5 RLBB17.pdf: 1009633 bytes, checksum: 32caa388e16efed87da156584575c5bb (MD5) license_text: 21936 bytes, checksum: 9833653f73f7853880c94a6fead477b1 (MD5) license_url: 49 bytes, checksum: 4afdbb8c545fd630ea7db775da747b2f (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) license.txt: 4244 bytes, checksum: 528b6a3c8c7d0c6e28129d576e989607 (MD5) Previous issue date: 2017enengLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)Cognitive radio networksRandom graphsStochastic geometryDynamic spectrum allocationFluid limitTelecomunicacionesEstimating the medium access probability in large cognitive radio networksPreprintinfo:eu-repo/semantics/preprintinfo:eu-repo/semantics/submittedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaRattaro, ClaudinaLarroca, FedericoBermolen, PaolaBelzarena, PabloTelecomunicacionesAnálisis de Redes, Tráfico y Estadísticas de 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- Universidad de la Repúblicafalse |
| spellingShingle | Estimating the medium access probability in large cognitive radio networks Rattaro, Claudina Cognitive radio networks Random graphs Stochastic geometry Dynamic spectrum allocation Fluid limit Telecomunicaciones |
| status_str | submittedVersion |
| title | Estimating the medium access probability in large cognitive radio networks |
| title_full | Estimating the medium access probability in large cognitive radio networks |
| title_fullStr | Estimating the medium access probability in large cognitive radio networks |
| title_full_unstemmed | Estimating the medium access probability in large cognitive radio networks |
| title_short | Estimating the medium access probability in large cognitive radio networks |
| title_sort | Estimating the medium access probability in large cognitive radio networks |
| topic | Cognitive radio networks Random graphs Stochastic geometry Dynamic spectrum allocation Fluid limit Telecomunicaciones |
| url | https://hdl.handle.net/20.500.12008/43525 |
