Banca de QUALIFICAÇÃO: JOSÉ MARTINS CASTRO NETO

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
DISCENTE : JOSÉ MARTINS CASTRO NETO
DATA : 04/12/2019
HORA: 10:00
LOCAL: Sala 108 do CETEC
TÍTULO:

Solution for LTE and Wi-Fi Coexistence in Multicell Environments

PALAVRAS-CHAVES:

coexistence, LTE-U, multicellular system, Wi-Fi, machine learning

PÁGINAS: 50
GRANDE ÁREA: Engenharias
ÁREA: Engenharia Elétrica
SUBÁREA: Telecomunicações
ESPECIALIDADE: Sistemas de Telecomunicações
RESUMO:

The increasing of internet access through fourth-generation (4G) mobile devices, coupled with the growing use of Smartphones and other connected devices, as well as the arrival of the fifth-generation (5G) and their massive use of streaming services devices, e.g., Netflix and Youtube, make the demand for mobile data transmission reaches high levels, and requires more bandwidth. However, the electromagnetic spectrum used for these applications is limited, resulting in a shortage demand, in addition to the high costs and bureaucracy to grant new bands, for example, the use of bands in millimeter waves (5G applications target). One of the solutions found for this problem is the exploitation of an unlicensed spectrum since it is free and has, in certain bands, higher bandwidth than the licensed, besides having underused portions, indicating less possibility of interference between technologies. In this context, LTE-LAA and LTE-U technologies arise for the exploration of unlicensed spectrum in the Industrial, Scientific and Medical (ISM) 5 GHz band, with modifications in the LTE media access mechanism. These technologies must coexist with the already established and successful Wi-Fi technology, which has been using the unlicensed spectrum since its inception. However, as each technology implements a different media access mechanism, studies should be conducted to indicate the impacts that each technology has on others when they coexist, i.e., when they compete to access the communication channel at the same time. In addition to the study of coexistence itself, there is the opportunity to apply Machine Learning techniques for the automatic adjustment of media access parameters, controlling the impact generated from one technology to another. Studies of such a scenario in an environment with only one access point of each technology have been extensively explored in the literature, but the study and design of solutions for the multicellular environment is a challenge. Thus, this work aims to: (1) The study of coexistence between LTE-U and Wi-Fi technologies in a multi-cellular scenario, with co-channel interference and inter-RAT interference (same technology); (2) application of Machine Learning algorithms for parameter adjustment to optimize the access to the medium of one or both technologies, and thereby achieve improved coexistence in terms of rate enhancement and packet loss reduction.

MEMBROS DA BANCA:
Externo ao Programa - 1840342 - MARCIO EDUARDO DA COSTA RODRIGUES
Interno - 3921178 - VALDEMIR PRAXEDES DA SILVA NETO
Presidente - 1412682 - VICENTE ANGELO DE SOUSA JUNIOR