Evaluation and Development of a Linear Regression-based 4G Long Term Evolution Path Loss Model for Rural Wireless Networks in Kurutie, Nigeria

Abstract

This study evaluated existing empirical path loss models and developed a linear regression-based propagation model for LTE networks operating at 2400 MHz in Kurutie, Delta State, Nigeria, a rural environment with dense vegetation and variable settlement patterns. Field measurements were collected along two routes using the Network Cell Info mobile application under clear weather conditions during two time slots to capture possible signal variations. Measured Reference Signal Received Power values were converted to path loss and compared with predictions from the Free Space Path Loss (FSPL) and Stanford University Interim (SUI) models, together with a site-specific linear regression model. The results showed clear differences between the empirical predictions and measured data. For Route 1, the SUI model overestimated path loss (mean = 140.23 dB; MBE = 33.86 dB), whereas FSPL underestimated attenuation (mean = 86.61 dB; MBE = -19.75 dB). The linear regression model produced lower errors, with RMSE = 14.29 dB, MAE = 9.38 dB, and MBE = -0.01 dB, explaining 29.7% of the variance after adjustment for sample size. However, five-fold cross-validation showed unstable performance (R² = -0.122 to 0.615). For Route 2, distance was not a statistically significant predictor of path loss (p = 0.126; R² = 0.020), indicating the influence of site-specific environmental factors. The findings support the need for local calibration and additional environmental variables in rural LTE path loss modelling.