Algorithm and software based on MLPNN for estimating channel use in the spectral decision stage in cognitive radio networks

dc.creatorHernández Viveros, Johana (1)
dc.creatorLópez Sarmiento, Danilo
dc.creatorVera, Nelson Enrique
dc.date.accessioned2019-05-24T09:06:25Z
dc.date.accessioned2023-03-07T19:21:41Z
dc.date.available2019-05-24T09:06:25Z
dc.date.available2023-03-07T19:21:41Z
dc.date.created2019-05-24T09:06:25Z
dc.identifier18196608
dc.identifierhttps://reunir.unir.net/handle/123456789/8287
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5902825
dc.description.abstractThe use of the multilayer perceptron neural networks (MLPNN) technique is proposed to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results they were generated by simulation, channel occupancy data sequences. The results show that the prediction percentage is greater than 60% in some of the tests carried out.
dc.languageeng
dc.publisherARPN Journal of Engineering and Applied Sciences
dc.relation;vol. 13, nº 6
dc.relationhttp://www.arpnjournals.com/jeas/volume_06_2018.htm
dc.rightsrestrictedAccess
dc.subjectcognitive radio
dc.subjectneural network
dc.subjectprediction
dc.subjectprimary user
dc.subjectScopus
dc.titleAlgorithm and software based on MLPNN for estimating channel use in the spectral decision stage in cognitive radio networks
dc.typeArticulo Revista Indexada


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