Path Loss Prediction Model Development in a Mountainous Forest Environment

IEEE Open Journal of the Communications Society

Kazuyoshi Takahashi¹  Bilguunmaa Myagmardulam²  Nakayama Tadachika²  Fumie Ono³  Toshinori Kagawa⁴  Fumihide Kojima⁵  Lin Shan⁶  Ryu Miura⁶ 

[1] Department of Civil and Environmental Engineering, Nagaoka University of Technology, Nagaoka, Japan;Department of Materials Science, Nagaoka University of Technology, Nagaoka, Japan;Global Strategy Bureau, Ministry of Internal Affairs and Communications, Tokyo, Japan;System Engineering Research Laboratory, Central Research Institute of Electric Power Industry, Yokosuka, Japan;Wireless Communication Center, National Institute of Information and Communications Technology, Yokosuka, Japan;Wireless Network Research Center, National Institute of Information and Communications Technology, Yokosuka, Japan;

关键词: Digital surface model;    LoRa;    path loss prediction;    modified empirical model;    drone mapper;   

DOI  :  10.1109/OJCOMS.2021.3122286

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown