Enhanced Path Loss Model by Image-Based Environmental Characterization

Accurate path loss (PL) models are critical for the design and optimization of wireless communication systems. The selection between empirical models and deterministic models are usually a tradeoff between accuracy and efficiency. In this letter, a novel environmental characterization method is defined by considering clutter information in the vector-based and image-based structures. Three PL models are proposed with different artificial neural network (ANN) architectures and two environmental characterizations. Comparative analysis shows that an image-based environmental characterization, which can reduce the influence of interference types, is better than a vector-based characterization. The combination of an image-based environmental characterization method and ANNs can enhance PL prediction in both accuracy and efficiency.