Controle de potência via algoritmo de enxame de vaga-lumes para atenuação dos efeitos da variação da temperatura ambiente em redes OCDMA

• Autor(a) principal: Cavali, Thiago dos Santos
• Data de Publicação: 2017
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT))
• Texto Completo: http://repositorio.utfpr.edu.br/jspui/handle/1/3357
• topic: Comunicações ópticas; Algorítmos computacionais; Controle de temperatura; Optical communications; Computer algorithms; Temperature control; CNPQ::ENGENHARIAS; Engenharia Elétrica

This work presents a research related to power control in OCDMA networks aiming to mitigate the effects of environmental temperature variation in optical fibers. The optical signal transmitted in fibers exposed to environmental temperature variation present a deformation on the optical signal autocorrelation function. This deformation causes a power loss that negatively affects the transmission quality in OCDMA networks. The proposed system considers a meta-heuristic based on firefly swarm behavior (FA – Firefly Algorithm) to control the allocated power to each user in network. This control aims to compensate the power penalty caused by different effects that affects the OCDMA networks, among them the environmental temperature variation. The usual power control is based on a mathematical method that uses a matrix inversion, having a high computational complexity, while the proposed approach reducers the computational effort for the problem resolution. The network structure and the optimization algorithm are implemented on MATLAB® environment. The obtained results show that environmental temperature variation, the network structure and the code construction parameters affects the performance of the OCDMA networks that uses 2-D and 3-D codes. It was possible to conclude that FA is an efficient approach to realize the power control in OCDMA networks, converging after a small number of iterations to optimum power values obtained by analytical methods and equivalent results when compared to other approaches in literature as, by example, Particle Swarm Optimization (PSO).