Prediction of Path Loss in Real-World Environments: Comparison of ITU-R P.1411 Models and Deep Learning

Accurate path loss estimation is essential for the design and optimization of wireless networks, especially in urban environments where propagation conditions can be extremely variable. This study compares traditional models such as the Free Space Path Loss (FSPL) model, ITU-R P.1411 model, and ITU-