(untitled) (International Journal of Latest Technology in Engineering Management & Applied Science, 2026)
The design and optimization of mobile communication networks depend heavily on accurate path loss prediction, especially in settings with complicated topography and changing meteorological conditions. The predicted accuracy of traditional empirical propagation models, such Hata and COST-231, is limited in heterogeneous situations since they mainly take distance and antenna parameters into consideration, frequently ignoring the combined impact of topographical variability and weather conditions. This study presents the empirical development of a terrain–meteorological path loss model for mobile networks in Bwari Area Council, Abuja, Nigeria. By combining important climatic factors like temperature, relative humidity, and rainfall with topography descriptors like elevation, building density, and vegetation, the suggested model expands upon the traditional log-distance formulation. Multiple linear regression techniques were employed to estimate model parameters after field measurements of received signal strength were gathered in various propagation settings. Improved statistical performance indicators, such as lower root mean square error (RMSE) and higher coefficient of determination (R2), show that the addition of environmental factors considerably improves prediction accuracy when compared to traditional models. The developed model is especially well-suited for deployment in tropical and heterogeneous environments because it successfully captures both spatial and temporal fluctuations in signal transmission. By offering an experimentally verified, environment-aware approach that enhances path loss prediction and facilitates effective mobile network planning and optimization, the study advances propagation modeling. For improving coverage estimation and network performance in comparable geographic areas, the suggested model provides a scalable method.