Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/11232
Título: SIRCo: uma arquitetura para Sensoriamento Inteligente de Rádios Cognitivos
Título(s) alternativo(s): ISCRa: an architecture for Intelligent Sensing for Cognitive Radios
Autores: Correia, Luiz Henrique A.
Correia, Luiz Henrique A.
Macedo, Daniel Fernandes
Lacerda, Wilian Soares
Palavras-chave: Rádio Cognitivo
Sensoriamento do espectro
Modelo de decisão do espectro
Rede Neural Articial
Cognitive Radio
Spectrum Management
Articial Neural Network
Spectrum decision model
Data do documento: 8-Jun-2016
Editor: Universidade Federal de Lavras
Citação: MARQUES, A. F. F. SIRCo: uma arquitetura para Sensoriamento Inteligente de Rádios Cognitivos. 2016. 151 p. Dissertação (Mestrado em Ciência da Computação)-Universidade Federal de Lavras, Lavras, 2016.
Resumo: The increased demand for using the Industrial, Scientific and Medical (ISM) unlicensed frequency spectrum has caused interference problems and lack of resource availability for wireless networks. Cognitive radio (CR) have emerged as an alternative to reduce interference and intelligently use the spectrum. Several protocols were proposed aiming to mitigate these problems, but most have not been implemented in real devices. This work presents an architecture for Intelligent Sensing for Cognitive Radios (ISCRa), and a spectrum decision model (SDM) based on Artificial Neural Networks (ANN), which uses as input a database with local spectrum behavior and a database with primary users information. For comparison, a spectrum decision model based on AHP, which employs advanced techniques in its spectrum decision method was implemented. Another spectrum decision model that considers only a physical parameter for channel classification was also implemented. Spectrum decision models evaluated, as well as ISCRa's architecture were developed in GNU-Radio framework and implemented on real nodes. Evaluation of SDMs considered metrics of: delivery rate, latency (Round Trip Time - RTT) and handoff. Experiments on real nodes showed that ISCRa architecture with ANN based SDM increased packet delivery rate and presented fewer frequency variation (handoff) while maintaining latency. Considering higher bandwidth as application's Quality of Service requirement, ANN-SDM obtained the best results when compared to other SDM for cognitive radio networks (CRN).
URI: http://repositorio.ufla.br/jspui/handle/1/11232
Aparece nas coleções:Ciência da Computação - Mestrado (Dissertações)

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