Optimization methods applied to nonlinear signal interference models

Página do item simplificado
dc.contributor.authorda Silva, M.
dc.contributor.authorSenne, E. L.F. [UNESP]
dc.contributor.authorVijaykumar, N. L.
dc.contributor.institutionApplied Computing, INPE - National Institute for Space Research
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionAssociated Laboratory of Computational Mathematics, INPE - National Institute for Space Research
dc.date.accessioned2018-12-11T16:39:16Z
dc.date.available2018-12-11T16:39:16Z
dc.date.issued2014-01-01
dc.description.abstractIn wireless mesh networks, it is important to establish the transmission capacity of the links, taking into account the presence of noise that interferes with the transmission and consequently degrades the signal sent from one device to another. This signal degradation is calculated from interference models, such as SNR (Signal-to-Noise Ratio), SIR (Signal-to-Interference Ratio) and SINR (Signal-to-Interference-plus-Noise Ratio). In these models, the link capacity is calculated according to a decreasing of power levels, depending on the noise or interference present, which needs to be adjusted to acceptable levels, in order to avoid committing the signal emission besides not causing health damage to people close to the device. Different models can be used to estimate the noise present in an environment. In wireless transmission, however, it is possible to calculate the noise by means of nonlinear equations, which are able to estimate the interference levels present in the network links. From these elements, it is possible to maximize the capacity of the network links, using models of nonlinear programming. As these models are difficult to be solved analytically, this work compares the results of different nonlinear programming models, based on the main interference models, with the results obtained by a classical approach for solving nonlinear models: The simulated annealing metaheuristic. In this paper, it will analyze the behavior of the heuristic algorithm, regarding the quality of the solution obtained and the processing time, as the network size increases.en
dc.description.affiliationApplied Computing, INPE - National Institute for Space Research
dc.description.affiliationDepartment of Mathematics, UNESP - São Paulo State University
dc.description.affiliationAssociated Laboratory of Computational Mathematics, INPE - National Institute for Space Research
dc.description.affiliationUnespDepartment of Mathematics, UNESP - São Paulo State University
dc.format.extent681-686
dc.identifier.citationEngineering Optimization IV - Proceedings of the 4th International Conference on Engineering Optimization, ENGOPT 2014, p. 681-686.
dc.identifier.scopus2-s2.0-84941955036
dc.identifier.urihttp://hdl.handle.net/11449/168024
dc.language.isoeng
dc.relation.ispartofEngineering Optimization IV - Proceedings of the 4th International Conference on Engineering Optimization, ENGOPT 2014
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.titleOptimization methods applied to nonlinear signal interference modelsen
dc.typeTrabalho apresentado em evento

Arquivos

Coleções

Artigos