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The modelling of tropical weather effects on ultra-high frequency (UHF) radio signals using SmartPLS

The interference occurs in radio signals transmission in many communication technologies are attributed to weather variations as well as other environmental factors. This work evaluates some atmospheric variables that have a dominating impact on temporal signal strength fluctuations. The Received...

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Main Authors: R., Mat, S.N, Hazmin, R., Umar, S., Ahmad, S.N.A.S., Zafar, M.S., Marhamah
Format: Conference or Workshop Item
Language:English
Published: 2018
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.unisza.edu.my/1600/1/FH03-ESERI-18-16516.pdf
http://eprints.unisza.edu.my/1600/
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spelling my-unisza-ir.16002020-11-18T07:36:23Z http://eprints.unisza.edu.my/1600/ The modelling of tropical weather effects on ultra-high frequency (UHF) radio signals using SmartPLS R., Mat S.N, Hazmin R., Umar S., Ahmad S.N.A.S., Zafar M.S., Marhamah T Technology (General) TA Engineering (General). Civil engineering (General) The interference occurs in radio signals transmission in many communication technologies are attributed to weather variations as well as other environmental factors. This work evaluates some atmospheric variables that have a dominating impact on temporal signal strength fluctuations. The Received Power Level (RPL) of Ultra High Frequency (UHF) communication signals (1800 MHz and 2160 MHz) and three tropical weather predictors (humidity, temperature and wind) were collected using spectrum analyser (KEYSIGHT N9915A) and weather station (Vantage Pro 2) respectively for 24 hours in rainy days. SmartPLS 3.2.6 was used to determine the strongest predictors influence the RPL for UHF frequency. It has been found that changes in weather conditions have affected the signal in which all weather predictors provide a significant relationship to the signal where R2 (coefficient of determination) value is 0.314 for frequency 1800 MHz and 0.254 for frequency 2160 MHz. The findings also show that humidity, temperature and wind are anticorrelations to RPL. However, humidity is found to be the strongest predictor influences the RPL of communication signals for frequency 1800 MHz (β= -0.449, p=0.000). This model may benefit many sectors such as telecommunication service provider, radio and TV transmission, radio astronomy study, Electromagnetic (EM) researcher and satellite broadcasting. 2018 Conference or Workshop Item NonPeerReviewed text en http://eprints.unisza.edu.my/1600/1/FH03-ESERI-18-16516.pdf R., Mat and S.N, Hazmin and R., Umar and S., Ahmad and S.N.A.S., Zafar and M.S., Marhamah (2018) The modelling of tropical weather effects on ultra-high frequency (UHF) radio signals using SmartPLS. In: The International Fundamentum Sciences Symposium 2018, 25-26 Jun 2018, Kuala Terengganu, Terengganu.
institution Universiti Sultan Zainal Abidin
building UNISZA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sultan Zainal Abidin
content_source UNISZA Institutional Repository
url_provider https://eprints.unisza.edu.my/
language English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
R., Mat
S.N, Hazmin
R., Umar
S., Ahmad
S.N.A.S., Zafar
M.S., Marhamah
The modelling of tropical weather effects on ultra-high frequency (UHF) radio signals using SmartPLS
description The interference occurs in radio signals transmission in many communication technologies are attributed to weather variations as well as other environmental factors. This work evaluates some atmospheric variables that have a dominating impact on temporal signal strength fluctuations. The Received Power Level (RPL) of Ultra High Frequency (UHF) communication signals (1800 MHz and 2160 MHz) and three tropical weather predictors (humidity, temperature and wind) were collected using spectrum analyser (KEYSIGHT N9915A) and weather station (Vantage Pro 2) respectively for 24 hours in rainy days. SmartPLS 3.2.6 was used to determine the strongest predictors influence the RPL for UHF frequency. It has been found that changes in weather conditions have affected the signal in which all weather predictors provide a significant relationship to the signal where R2 (coefficient of determination) value is 0.314 for frequency 1800 MHz and 0.254 for frequency 2160 MHz. The findings also show that humidity, temperature and wind are anticorrelations to RPL. However, humidity is found to be the strongest predictor influences the RPL of communication signals for frequency 1800 MHz (β= -0.449, p=0.000). This model may benefit many sectors such as telecommunication service provider, radio and TV transmission, radio astronomy study, Electromagnetic (EM) researcher and satellite broadcasting.
format Conference or Workshop Item
author R., Mat
S.N, Hazmin
R., Umar
S., Ahmad
S.N.A.S., Zafar
M.S., Marhamah
author_facet R., Mat
S.N, Hazmin
R., Umar
S., Ahmad
S.N.A.S., Zafar
M.S., Marhamah
author_sort R., Mat
title The modelling of tropical weather effects on ultra-high frequency (UHF) radio signals using SmartPLS
title_short The modelling of tropical weather effects on ultra-high frequency (UHF) radio signals using SmartPLS
title_full The modelling of tropical weather effects on ultra-high frequency (UHF) radio signals using SmartPLS
title_fullStr The modelling of tropical weather effects on ultra-high frequency (UHF) radio signals using SmartPLS
title_full_unstemmed The modelling of tropical weather effects on ultra-high frequency (UHF) radio signals using SmartPLS
title_sort modelling of tropical weather effects on ultra-high frequency (uhf) radio signals using smartpls
publishDate 2018
url http://eprints.unisza.edu.my/1600/1/FH03-ESERI-18-16516.pdf
http://eprints.unisza.edu.my/1600/
_version_ 1684657724171747328
score 13.211869

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