Meta-Heurísticas aplicadas ao problema de alocação de sequências piloto em sistemas massive mimo

• Ano de defesa: 2021
• Autor(a) principal: Matos, Everton Alex
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Cornelio Procopio; Brasil; Programa de Pós-Graduação em Informática; UTFPR
• Palavras-chave em Português: Algoritmos; Algoritmos genéticos; Telecomunicações; Algorithms; Genetic algorithms; Telecommunication; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO; Ciência da Computação
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/30236

The fifth generation of modern telecommunications systems, the 5G, came up with the challenge of incrementing the spectral and energetic efficiencies of communications systems. To reach this objective, one of the employed technologies is the massive use of antennas on the base station, a method known as Massive MIMO. The system uses space diversity to allow the transmission of downlink and uplink without interference by training it with orthogonal sequences. However, as the number of users on the system grows, the size of the sequences also grows in order to ensure orthogonality. This causes an efficiency reduction on the system. For this reason, it is necessary to reuse the pilot sequences, which leads to the phenomenon known as pilot contamination, where different users interfere with the signals for other users degrading the performance of the communication link. To get around this problem and minimize the pilot contamination impact on communications, optimization techniques can be applied to the allocation process of the pilot sequences with the objective to maximize the spectral efficiency of the system. Therefore, this work shows the application of different meta-heuristics to solve the pilot sequence allocation problem, as well as the development of a public dataset in order to test the solutions in different mobile communications scenarios.