AMPLE: An Adaptive Multiple Path Loss Exponent Radio Propagation Model Considering Environmental Factors

TL;DR

To the best of the knowledge, this is the first time that a multi-slope model precisely maps PLEs and region types and can be integrated into map systems by creating a new path loss attribute for digital maps.

Abstract

We present AMPLE -- a novel multiple path loss exponent (PLE) radio propagation model that can adapt to different environmental factors. The proposed model aims at accurately predicting path loss with low computational complexity considering environmental factors. In the proposed model, the scenario under consideration is classified into regions from a raster map, and each type of region is assigned with a PLE. The path loss is then computed based on a direct path between the transmitter (Tx) and receiver (Rx), which records the intersected regions and the weighted region path loss. To regress the model, the parameters, including PLEs, are extracted via measurement and the region map. We also verify the model in a suburban area. To the best of our knowledge, this is the first time that a multi-slope model precisely maps PLEs and region types. Besides, this model can be integrated into map systems by creating a new path loss attribute for digital maps.

Figures (5)

• Figure 1: The process of constructing the AMPLE model.
• Figure 2: One example of raster map classification, from the original raster map to the region map, along with lengths of the intersected regions (e.g., $d_{0}$ and $d_{1}$ are the close-in distance and length of the first region, respectively).
• Figure 3: The scatter plot of measurement and estimation results of least-squares (LS) and maximum likelihood (ML) with truncated normal distribution.
• Figure 4: Map classification in partial Sheffield City, from the original raster map to the region map, along with the pixel coordinate system.
• Figure 5: Heatmaps of the path loss prediction results predicted by (a) the AMPLE model and (b) the log-distance model.