Algoritmos baseados em estratégia evolutiva para a seleção dinâmica de espectro em rádios cognitivos

• Autor(a) principal: Barbosa, Camila Soares
• Data de Publicação: 2013
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• dARK ID: ark:/38995/001300000dvdr
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/3706
• topic: Rádios cognitivos; Seleção dinâmica de espectro; Estratégias evolutivas; Cognitive radio; Dynamic spectrum selection; Evolutionary strategies; CIENCIA DA COMPUTACAO::TEORIA DA COMPUTACAO

One of the main challenges in Dynamic Spectrum Selection for Cognitive Radios is the choice of the frequency range for each transmission. This choice should minimize interference with legacy devices and maximize the discovering opportunities or white spaces. There are several solutions to this issue, and Reinforcement Learning algorithms are the most successful. Among them stands out the Q-Learning whose weak point is the parameterization, since adjustments are needed in order to reach successfully the proposed objective. In that sense, this work proposes an algorithm based on evolutionary strategy and presents the main characteristics adaptability to the environment and fewer parameters. Through simulation, the performance of the Q-Learning and the proposal of this work were compared in different scenarios. The results allowed to evaluate the spectral efficiency and the adaptability to the environment. The proposal of this work shows promising results in most scenarios.