The Modelling of Tropical Weather Effects on Ultra-High Frequency (UHF) Radio Signals Using SmartPLS

International Fundamentum Science Symposium 2018

自然科学;工业技术

Mat, R.^1,4 ; Hazmin, S.N.^1,5 ; Umar, R.^2 ; Ahmad, S.^3 ; Zafar, S.N.A.S.^2 ; Marhamah, M.S.^2

Advanced Nano Materials (ANoMa) Research Group, School of Fundamental Science, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu

21030, Malaysia^1

East Coast Environmental Research Institute (ESERI), Universiti Sultan Zanal Abidin, Kampus Gong Badak, Kuala Nerus, Terengganu

21300, Malaysia^2

School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu

21030, Malaysia^3

Institut Pendidikan Guru Kampus Sultan Mizan, Besut Terengganu

22200, Malaysia^4

Pusat Islam Sultan Mahmud, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu

21030, Malaysia^5

关键词: Atmospheric variables;    Coefficient of determination;    Communication signals;    Communication technologies;    Satellite broadcasting;    Telecommunication service provider;    Ultra High Frequency (UHF);    Ultra-high-frequency communications;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/440/1/012041/pdf
DOI  :  10.1088/1757-899X/440/1/012041

来源: IOP

【 摘 要 】

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.