Simulation of signal separation using MIMO model over fading channels

Multiple-Input Multiple-Output (MIMO) communication models are generally used for diversity in data transmission. These can also be developed to transmit different data at the same time, with corresponding receivers, and separate them upon receiving. In effect, this promotes frequency conservation b...

Full description

Saved in:
Bibliographic Details
Main Authors: Altarejos, Louie Ernest F., Chua, Patricia Monserrat O., Nogales, Giancarlo P., Seelinkit, Jennifer L.
Format: text
Language:English
Published: Animo Repository 2006
Subjects:
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/14284
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: De La Salle University
Language: English
id oai:animorepository.dlsu.edu.ph:etd_bachelors-14926
record_format eprints
spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-149262021-11-15T13:30:58Z Simulation of signal separation using MIMO model over fading channels Altarejos, Louie Ernest F. Chua, Patricia Monserrat O. Nogales, Giancarlo P. Seelinkit, Jennifer L. Multiple-Input Multiple-Output (MIMO) communication models are generally used for diversity in data transmission. These can also be developed to transmit different data at the same time, with corresponding receivers, and separate them upon receiving. In effect, this promotes frequency conservation because a MIMO model can utilize the use of a single frequency bandwidth. In this study, a simulation of signal separation using a MIMO model is discussed with the aid of other methods to accomplish it. Two randomly generated signals are 8PSK modulated before transmission. The mixing occurs in the Rayleigh fading channel, wherein the mixing matrix is generated to conduct the actual addition of the transmitted signals. AWGN is included in the mixing process to define the noise and simulate thermal noise. At the receivers, the initial method applied is the conventional Equivariant Adaptive Source separation via Independence (EASI) algorithm. This serially determines the inverse of the mixing matrix of the channel to be able to separate the transmitted signals. After that, the signals pass through the normalized EASI algorithm, wherein the last mixing coefficient of the conventional EASI algorithm is the initial value for this section. A rotator follows the normalized EASI algorithm to correct the separated signals to its proper phase angles. The last step is demodulation, since both signals are originally 8PSK modulated. Included in the study is a graphical user interface (GUI) layout of the simulation that can be easily manipulated and for ease of viewing of the simulation. 2006-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/14284 Bachelor's Theses English Animo Repository Communication and technology Data transmission systems Frequency relays Engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Communication and technology
Data transmission systems
Frequency relays
Engineering
spellingShingle Communication and technology
Data transmission systems
Frequency relays
Engineering
Altarejos, Louie Ernest F.
Chua, Patricia Monserrat O.
Nogales, Giancarlo P.
Seelinkit, Jennifer L.
Simulation of signal separation using MIMO model over fading channels
description Multiple-Input Multiple-Output (MIMO) communication models are generally used for diversity in data transmission. These can also be developed to transmit different data at the same time, with corresponding receivers, and separate them upon receiving. In effect, this promotes frequency conservation because a MIMO model can utilize the use of a single frequency bandwidth. In this study, a simulation of signal separation using a MIMO model is discussed with the aid of other methods to accomplish it. Two randomly generated signals are 8PSK modulated before transmission. The mixing occurs in the Rayleigh fading channel, wherein the mixing matrix is generated to conduct the actual addition of the transmitted signals. AWGN is included in the mixing process to define the noise and simulate thermal noise. At the receivers, the initial method applied is the conventional Equivariant Adaptive Source separation via Independence (EASI) algorithm. This serially determines the inverse of the mixing matrix of the channel to be able to separate the transmitted signals. After that, the signals pass through the normalized EASI algorithm, wherein the last mixing coefficient of the conventional EASI algorithm is the initial value for this section. A rotator follows the normalized EASI algorithm to correct the separated signals to its proper phase angles. The last step is demodulation, since both signals are originally 8PSK modulated. Included in the study is a graphical user interface (GUI) layout of the simulation that can be easily manipulated and for ease of viewing of the simulation.
format text
author Altarejos, Louie Ernest F.
Chua, Patricia Monserrat O.
Nogales, Giancarlo P.
Seelinkit, Jennifer L.
author_facet Altarejos, Louie Ernest F.
Chua, Patricia Monserrat O.
Nogales, Giancarlo P.
Seelinkit, Jennifer L.
author_sort Altarejos, Louie Ernest F.
title Simulation of signal separation using MIMO model over fading channels
title_short Simulation of signal separation using MIMO model over fading channels
title_full Simulation of signal separation using MIMO model over fading channels
title_fullStr Simulation of signal separation using MIMO model over fading channels
title_full_unstemmed Simulation of signal separation using MIMO model over fading channels
title_sort simulation of signal separation using mimo model over fading channels
publisher Animo Repository
publishDate 2006
url https://animorepository.dlsu.edu.ph/etd_bachelors/14284
_version_ 1772834973540155392