1. Repositório Institucional - Universidade Federal de Uberlândia
  2. Faculdade de Engenharia Elétrica (FEELT)
  3. TESE - Engenharia Elétrica
Please use this identifier to cite or link to this item: https://repositorio.ufu.br/handle/123456789/19062
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dc.creatorMata, Saulo Henrique da-
dc.date.accessioned2017-07-06T11:51:18Z-
dc.date.available2017-07-06T11:51:18Z-
dc.date.issued2017-05-22-
dc.identifier.citationMATA, Saulo Henrique da. A new genetic algorithm based scheduling algorithm for the LTE Uplink. 2017. 120 f. Dissertação (Mestrado em Ciências) - Universidade Federal de Uberlândia, Uberlândia, 2017. DOI http://doi.org/10.14393/ufu.te.2017.121pt_BR
dc.identifier.urihttps://repositorio.ufu.br/handle/123456789/19062-
dc.languageporpt_BR
dc.publisherUniversidade Federal de Uberlândiapt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectEngenharia elétricapt_BR
dc.subjectLong-Term Evolution (Telecomunicações)pt_BR
dc.subjectAlgoritmos genéticospt_BR
dc.subjectIndex-termspt_BR
dc.subjectLTEpt_BR
dc.subjectUplinkpt_BR
dc.subjectSchedulingpt_BR
dc.subjectAlgorithmspt_BR
dc.subjectGenetic Algorithmspt_BR
dc.subjectns-3pt_BR
dc.titleA new genetic algorithm based scheduling algorithm for the LTE Uplinkpt_BR
dc.typeTesept_BR
dc.contributor.advisor1Guardieiro, Paulo Roberto-
dc.contributor.advisor1Latteshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4787857H7pt_BR
dc.contributor.referee1Borin, Juliana Freitag-
dc.contributor.referee1Latteshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4731432T0pt_BR
dc.contributor.referee2Teixeira, Márcio Andrey-
dc.contributor.referee2Latteshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4744281U2pt_BR
dc.contributor.referee3Silva, Éderson Rosa da-
dc.contributor.referee3Latteshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4479414D5pt_BR
dc.contributor.referee4Cunha, Marcio José da-
dc.contributor.referee4Latteshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4779066Z6pt_BR
dc.creator.Latteshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4329033J4pt_BR
dc.description.degreenameTese (Doutorado)pt_BR
dc.description.resumoLong Term Evolution has become the de facto technology for the 4G networks. It aims to deliver unprecedented data transmission rates and low latency for several types of applications and services. In this context, this thesis investigates the resource allocation in the LTE uplink. From the principle that resource allocation in the uplink is a complex optimization problem, the main contribution of this thesis is a novel scheduling algorithm based on Genetic Algorithms (GA). This algorithm introduces new operations of initialization, crossover, mutation and a QoS-aware fitness function. The algorithm is evaluated in a mixed traffic environment and its performance is compared with relevant algorithms from the literature. Simulations were carried out in ns-3 and the results show that the proposed algorithm is able to meet the Quality of Service (QoS) requirements of the applications, while presenting a satisfactory execution time.pt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.programPrograma de Pós-graduação em Engenharia Elétricapt_BR
dc.sizeorduration120pt_BR
dc.subject.cnpqCNPQ::ENGENHARIAS::ENGENHARIA ELETRICApt_BR
dc.identifier.doihttp://doi.org/10.14393/ufu.te.2017.121pt_BR
dc.orcid.putcode81755145-
dc.crossref.doibatchid58434145-d6ec-45ce-b3f5-4a5d7e4364e9-
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