Path Loss Prediction on Earth-Space Link Using Statistical and Time Series Approach at Ka-Band in Abuja, North Central Nigeria

Abstract Predictive path loss modelling is essential in designing wireless communication systems. However, the empirical methods of path loss prediction are inaccurate as the empirical models cannot be implemented outside the area or region where they are developed. This study focuses on improving the prediction of path loss using statistical approaches such as multiple linear regression (MLR) and time series models using eight (2014 – 2021) data retrieved from the global precipitation measuring mission (GPM) at Ka-band. The step-wise selected method was adopted for the multiple linear regression (MLR). In the exponential smoothing method, weighting is carried out exponentially, decreasing in the direction of the older values. The MLR analysis revealed that the MLR model performs well, with an accuracy of 99.52%. The R 2 value of 99.52% indicated a strong correlation between the estimated and predicted path loss in the model. PL = 18.706-0.98459 P r +1.60027 P t +0.99808 G r The P-value of the regression model is 0.000, indicating that the model estimated by the MLR procedure is statistically significant at a level of 0.05. Also, the results showed that the transmitted antenna gain is the most contributed predictor in the path loss with a value of 1.60027 dB. Likewise, the results from the exponential smoothing models revealed that the single exponential smoothing (SES) model performs better than the double exponential smoothing model with a mean absolute percentage error (MAPE) of 14.47%, indicating that the model’s performance is good because the MAPE value falls within 10 – 20%. The mean absolute deviation (MAD), mean square deviation (MSD), and smoothing constant are 0.3215, 0.2313, and 0.9685, respectively. Striking a balance, the application of MLR and the SES models will improve wireless communication systems in Abuja, the North Central region of Nigeria, at Ka-band. Therefore, engineers and policymakers in the Nigerian telecommunication industry should assess the impacts of path loss within the study locations towards sustainable telecommunications and infrastructure (SDG goal 9) for planning and setting radiowave propagation technologies in the study locations and Nigeria at large.

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Publication Details

Journal
IOP Conference Series Earth and Environmental Science
Published
2024-12-01
DOI
https://doi.org/10.1088/1755-1315/1428/1/012018
Primary Topic
Millimeter-Wave Propagation and Modeling
Type
article
Field-Weighted Citation Impact
0.00
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article

Path Loss Prediction on Earth-Space Link Using Statistical and Time Series Approach at Ka-Band in Abuja, North Central Nigeria

T. V. Omotosho, T. E. Arijaje, A. P. Aizebeokhai
IOP Conference Series Earth and Environmental Science
Millimeter-Wave Propagation and Modeling
article

Path Loss Prediction on Earth-Space Link Using Statistical and Time Series Approach at Ka-Band in Abuja, North Central Nigeria

T. V. Omotosho, T. E. Arijaje, A. P. Aizebeokhai
article en

Abstract

Abstract Predictive path loss modelling is essential in designing wireless communication systems. However, the empirical methods of path loss prediction are inaccurate as the empirical models cannot be implemented outside the area or region where they are developed. This study focuses on improving the prediction of path loss using statistical approaches such as multiple linear regression (MLR) and time series models using eight (2014 – 2021) data retrieved from the global precipitation measuring mission (GPM) at Ka-band. The step-wise selected method was adopted for the multiple linear regression (MLR). In the exponential smoothing method, weighting is carried out exponentially, decreasing in the direction of the older values. The MLR analysis revealed that the MLR model performs well, with an accuracy of 99.52%. The R 2 value of 99.52% indicated a strong correlation between the estimated and predicted path loss in the model. PL = 18.706-0.98459 P r +1.60027 P t +0.99808 G r The P-value of the regression model is 0.000, indicating that the model estimated by the MLR procedure is statistically significant at a level of 0.05. Also, the results showed that the transmitted antenna gain is the most contributed predictor in the path loss with a value of 1.60027 dB. Likewise, the results from the exponential smoothing models revealed that the single exponential smoothing (SES) model performs better than the double exponential smoothing model with a mean absolute percentage error (MAPE) of 14.47%, indicating that the model’s performance is good because the MAPE value falls within 10 – 20%. The mean absolute deviation (MAD), mean square deviation (MSD), and smoothing constant are 0.3215, 0.2313, and 0.9685, respectively. Striking a balance, the application of MLR and the SES models will improve wireless communication systems in Abuja, the North Central region of Nigeria, at Ka-band. Therefore, engineers and policymakers in the Nigerian telecommunication industry should assess the impacts of path loss within the study locations towards sustainable telecommunications and infrastructure (SDG goal 9) for planning and setting radiowave propagation technologies in the study locations and Nigeria at large.

IOP Conference Series Earth and Environmental ScienceVol. 1428(1)
Covenant University (NG)
Openalex Percentile: Top 55%
Millimeter-Wave Propagation and Modeling
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