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

Mat, Roshidah; Hazmin, S.N.; Umar, Roslan; Sabri, Ahmad; Zafar, Sharifah Nurul Aisyah Syed; Marhamah, M.S.

doi:10.1088/1757-899x/440/1/012041

Cited by 10 publications

(10 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although there are good studies to understand and establish the relationships between weather conditions and radio link quality, there are only a few pieces of work in the scope of our problem statement i.e., to predict RLF subjected to weather adversities. The research work in [7], [8] establish that there is negative correlation between signal strength and humidity, whereas temperature seems to be positively correlated with signal strength. In a study on impact of humidity and temperature on radio signal quality [9], the authors claim that temperature plays a significant role, as compared to humidity, in determining the grade of a given radio channel in the ISM band.…”

Section: Related Workmentioning

confidence: 94%

“…The authors modeled the received signal under such conditions and they found that it would fit Rician-K distribution wherein the K-factor would decrease as the wind or rain gets intensified. Effects of weather conditions on radio link quality in Ultra-High Frequency (UHF) in a tropical region were examined in [8]. With their work they could establish that there is an anti-correlation between radio link quality and weather parameters like wind, humidity and temperature, with humidity being the strongest influencer.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

AI powered solution for radio link failure prediction based on link features and weather forecast

Priyanshu¹,

Giri²,

Shachi³

et al. 2022

ITU J-FET

View full text Add to dashboard Cite

Radio link sustainability gets affected by weather adversities such as snow, fog, cloud, rain, thunderstorm, etc. A proactive solution in radio link failure scenarios is necessary to overcome economic loss and maintain the Quality of Service (QoS). To address the issue, our work contributes towards building a machine-learning-based solution to predict the radio link failure when generic regional weather forecast data, key performance indices of radio link and spatial nature of the data are available. After rigorous data preprocessing, ensembling models like logistic regression, random forest, light BGM, XGBoost and gradient boosting classifiers were trained to predict the Radio Link Failure (RLF) for two cases i.e., day-1-predict and day-5-predict. Since it is a classification use case, the metrics used for our work are precision, recall, and F1 score. The performance of the gradient boosting classifier was better as compared to the other models with an F1 score of 0.95 for both day-1-predict and day-5-predict.

show abstract

Section: Related Workmentioning

confidence: 94%

Section: Related Workmentioning

confidence: 99%

AI powered solution for radio link failure prediction based on link features and weather forecast

Priyanshu¹,

Giri²,

Shachi³

et al. 2022

ITU J-FET

View full text Add to dashboard Cite

show abstract

“…Studies have been carried out by several researchers to explore the effect of atmospheric elements on radio waves [28][29][30][31][32][33][34][35][36], but the results and conclusions have been contradictory. Some research studies claim that relative humidity is the main factor while others claim that temperature is the dominating factor [37][38][39][40].…”

Section: Original Research Articlementioning

confidence: 99%

Tropospheric Influence on Low-band Very High Frequency (VHF) Radio Waves

Ekah

Obi

Ewona

2022

AJARR

View full text Add to dashboard Cite

The objectives of this study are to understudy the effects of temperature and relative humidity on low-band VHF signals, obtain a propagation model for signal transmission over Calabar and to ascertain the suitability of the free space propagation model for the study terrain. Results obtained shows that temperature and relative humidity has no effect on low-band VHF signals. The suitability of the free space propagation model for the study terrain failed, as calculated results underestimated path losses in the study area. Multiple regression analysis was used to obtain a suitable propagation model for the study terrain. However, since the studied meteorological variables has no effect on low-band VHF signals in the study area, the measured path losses could be attributed to foliage, hills, distance away from the transmitter and other components of the study terrain in which the signal is propagated.

show abstract

“…In this region, signals, usually transmitted as radio waves [14,15], are affected by varying conditions during propagation and when a radio wave is interrupted by bad weather, signal quality reduces and this can cause signal losses [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Tropospheric Influence on Call Setup in Mobile Networks

Ekah

Onuu²

2022

JERR

View full text Add to dashboard Cite

The dependency of mobile network operators on the troposphere for signal transmission without pre-evaluation and characterization of the region where the signals are transmitted is the reason for the poor Quality of Services (QoS) delivered to their network subscribers. To describe the reliability of networks, one needs to know which weather parameters affect the propagation of signals. This research investigates the effect of weather variables (relative humidity, wind speed, rainfall and temperature) on call setup for four mobile networks (MTN, Airtel, Globacom and 9mobile) in Cross River State, Nigeria. Six years data of weather variables collected from the Nigerian Meteorological Agency (NiMet) and six years Call Setup Success Rate (CSSR) data obtained from the telecommunications regulatory body, Nigerian Communication Commission (NCC), was used in this study, both spanning from January 2015 to December 2020. From the collected data, graphs were plotted and, in each case, the CSSR was the dependent variable while the tropospheric variables were the independent variables. Also, regression models were obtained to forecast the CSSR of each network, provided the tropospheric variable at each given period is known. Finally, the variables were correlated to give a picture of how each tropospheric variable related to the CSSR of the networks. For MTN network, a low negative correlation was obtained for temperature and relative humidity, a low positive correlation was obtained for rainfall while an increase in windspeed led to a corresponding decrease in CSSR. For Airtel network, a moderately positive correlation existed between CSSR and windspeed/rainfall while a low positive relationship existed between temperature and CSSR. However, an increase in relative humidity led to more successful call setups. For Globacom network an increase in relative humidity, windspeed, and temperature moderately led to a decrease in the number of successful call setups while rainfall had a very low effect on call setup. Finally, for 9mobile network, an increase in temperature led to a moderate increase in call setup. Relative humidity and windspeed had a negligible effect on call setup while a moderately negative relationship existed between rainfall and call setup. The result of this study will be very useful to mobile network planners and the network operators.

show abstract

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

Cited by 10 publications

References 13 publications

AI powered solution for radio link failure prediction based on link features and weather forecast

AI powered solution for radio link failure prediction based on link features and weather forecast

Tropospheric Influence on Low-band Very High Frequency (VHF) Radio Waves

Tropospheric Influence on Call Setup in Mobile Networks

Contact Info

Product

Resources

About