Sistema de transmisión multiportadora mediante multiplexación por división de frecuencia generalizado (GFDM)
Telecommunications have contributed to the development of society, its improvement, is closely related with the changes and technological advances, that is the reason why the communication systems have been adapting according with the needs and increasingly demanding requirements of the users. I...
Autor Principal: | Flores Tipán, Lizeth Carolina |
---|---|
Otros Autores: | Toscano Lucero, Lisbeth Carolina |
Formato: | bachelorThesis |
Idioma: | spa |
Publicado: |
2017
|
Materias: | |
Acceso en línea: |
http://dspace.ups.edu.ec/handle/123456789/14023 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Sumario: |
Telecommunications have contributed to the development of society, its improvement,
is closely related with the changes and technological advances, that is the reason why
the communication systems have been adapting according with the needs and
increasingly demanding requirements of the users.
In order to optimize the use of the frequency spectrum, new multicarrier systems have
been proposed as the key to the 5G infrastructure, GFDM (Generalized Frequency
Division Multiplexing) is including among them. It works with an envelope processing
method to the filtering, making the data frame smaller and achieving a delay in
milliseconds.
For a better understanding the operation of Generalized Frequency Division
Multiplexing, this project implements an off - line multicarrier transmission system,
using Matlab 2013 as simulation tool, and signal analyzer equipment in both time and
frequency domain.
On the development of this work a transmission of random data is performed, which
are firstly subjected to 16-QAM modulation, then passed to the GFDM process
through the application of the RRC (Root Raised Cosine) rectangular filter, and finally
obtain the transmission signal. Then the signal is generated trough AWG generator,
and observed by the Real Time Oscilloscope, after that received data is processed in
Matlab again. At the end, an analysis of the data sent and received is performed, using
parameters such as BER (Bit Error Rate) and EVM (Error Vector Magnitude), the first
allows to know how much error exists between the transmitted and received bits,
second one evaluates the QAM symbols in both transmission and reception. |
---|