Please use this identifier to cite or link to this item:
https://repositorio.ufu.br/handle/123456789/19062
Document type: | Tese |
Access type: | Acesso Aberto |
Title: | A new genetic algorithm based scheduling algorithm for the LTE Uplink |
Author: | Mata, Saulo Henrique da |
First Advisor: | Guardieiro, Paulo Roberto |
First member of the Committee: | Borin, Juliana Freitag |
Second member of the Committee: | Teixeira, Márcio Andrey |
Third member of the Committee: | Silva, Éderson Rosa da |
Fourth member of the Committee: | Cunha, Marcio José da |
Summary: | Long Term Evolution has become the de facto technology for the 4G networks. It aims to deliver unprecedented data transmission rates and low latency for several types of applications and services. In this context, this thesis investigates the resource allocation in the LTE uplink. From the principle that resource allocation in the uplink is a complex optimization problem, the main contribution of this thesis is a novel scheduling algorithm based on Genetic Algorithms (GA). This algorithm introduces new operations of initialization, crossover, mutation and a QoS-aware fitness function. The algorithm is evaluated in a mixed traffic environment and its performance is compared with relevant algorithms from the literature. Simulations were carried out in ns-3 and the results show that the proposed algorithm is able to meet the Quality of Service (QoS) requirements of the applications, while presenting a satisfactory execution time. |
Keywords: | Engenharia elétrica Long-Term Evolution (Telecomunicações) Algoritmos genéticos Index-terms LTE Uplink Scheduling Algorithms Genetic Algorithms ns-3 |
Area (s) of CNPq: | CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
Language: | por |
Country: | Brasil |
Publisher: | Universidade Federal de Uberlândia |
Program: | Programa de Pós-graduação em Engenharia Elétrica |
Quote: | MATA, Saulo Henrique da. A new genetic algorithm based scheduling algorithm for the LTE Uplink. 2017. 120 f. Dissertação (Mestrado em Ciências) - Universidade Federal de Uberlândia, Uberlândia, 2017. DOI http://doi.org/10.14393/ufu.te.2017.121 |
Document identifier: | http://doi.org/10.14393/ufu.te.2017.121 |
URI: | https://repositorio.ufu.br/handle/123456789/19062 |
Date of defense: | 22-May-2017 |
Appears in Collections: | TESE - Engenharia Elétrica |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
NewGeneticAlgorithm.pdf | 17.08 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.