Escalonamento de pacotes e gerenciamento de interferência em redes heterogêneas baseados na teoria dos jogos

Detalhes bibliográficos
Ano de defesa: 2021
Autor(a) principal: Moreira, Júnio
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Uberlândia
Brasil
Programa de Pós-graduação em Engenharia Elétrica
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://repositorio.ufu.br/handle/123456789/31573
http://doi.org/10.14393/ufu.te.2021.176
Resumo: Cellular networks are expected to provide broadband access to a continuously growing number of mobile users. The densification of cellular networks is essential to increase its capacity and improve spectral efficiency, however, inter-cell interference still represents a challenge that limits system performance, especially for users located at the edge of the cell. Therefore, it is necessary to coordinate the allocation of resources between base stations and to minimize interference efficiently. This work presents a framework for packet scheduling and interference management for heterogeneous networks based on Game Theory. As a proposed solution, it is implemented a packet scheduler for heterogeneous networks in downlink LTE-A based on game theory, through the Colonel Blotto algorithm. The proposed algorithm is evaluated by means of computer simulation, comparing it with relevant algorithms in the literature. The results of the simulations demonstrated that the scheduler is able to achieve a better performance in terms of energy efficiency, spectral efficiency and fairness, while presenting a much lower execution time compared to another scheduler based on Game Theory. Moreover, the Exact Potential Game Theory is used for interference management of the enhanced Inter-Cell Interference Coordination (eICIC) and Further eICIC (FeICIC) techniques. In addition, an extension of eICIC optimization is implemented through a modified utility function, called eICIC+ optimization. The results of the simulations illustrate the important performance gain obtained by eICIC+ optimization and especially for users at the edge of the cell, where the results showed better fairness and throughput, compared to eICIC optimization.