Optimizing the Egli Model for Vehicular Ultra-Shortwave Communication Using High-Resolution Remote Sensing Satellite...

Area of Science:

• Wireless Communication
• Radio Wave Propagation
• Remote Sensing

Background:

• Traditional radio wave propagation models have limitations for vehicular ultra-shortwave communication path loss prediction.
• Accurate path loss prediction is essential for reliable vehicular wireless systems.

Purpose of the Study:

• To propose an optimized Egli model using high-resolution remote sensing satellite imagery for vehicular ultra-shortwave communication.
• To enhance the accuracy of path loss prediction in vehicular communication environments.

Main Methods:

• Calculating equivalent antenna height using satellite imagery and terrain data.
• Developing an equivalent ground loss substitution method from satellite-derived surface information.
• Applying the least squares method (LSM) to fit relief height within the Egli model framework.

Main Results:

• The optimized Egli model demonstrated a significant reduction in average error compared to the traditional Egli model and models with correction factors.
• The optimized model achieved an average error of 0.45%, outperforming existing methods.
• Validation confirmed the model's accuracy by comparing theoretical calculations with measured data.

Conclusions:

• The proposed optimized Egli model effectively addresses limitations in predicting path loss for vehicular ultra-shortwave communication.
• Integration of high-resolution remote sensing data significantly enhances model performance.
• The optimized model offers improved suitability for real-world vehicular communication systems.