Path Loss Prediction Model Development in a Mountainous Forest Environment

Abstract

We consider a method for developing a radio-wave propagation prediction model in a mountainous forested area. A new path loss development approach uses a free-space path loss (FSPL) model and an empirical path loss model. To improve the prediction accuracy, the transmission path distance, free space area, and forest area were calculated separately. We obtained the transmission path distance for free space and forest areas from the digital surface model (DSM), which represents surface elevation information, including vegetation and object height. In this study, the results showed that by combining the empirical model with FSPL for free space area, the accuracy for all the empirical models was improved. We confirmed that the transmission distance calculation of the free space area and forest area with a combination of the empirical models showed a better performance than the model with physical distance. The predicted model results were validated using the actual radio wave propagation in the 920 MHz band measurement data. The overall path loss prediction accuracy was improved for the empirical models average of 8.05 dB on the experimental data.

Keywords

• Digital surface model
• LoRa
• path loss prediction
• modified empirical model
• drone mapper