The special case of Egli and Hata model optimization using least-square approximation method

Abstract

Terrestrial signal loss prediction for the VHF band is limited to a few models. With perpetual prominence in its application, understanding VHF signal variation in a different scenario stimulates interests and demand for ruling out a decent performing model applicable in the VHF band. This paper aims to optimize the selected model using measurement data for the precise deployment of cellular mobile signal over the study area. We chose the least-square regression fitting method and applied it to Egli and Hata model for improved prediction with measurement data made over a vast hilly forested area. We observed that optimized models of Egli and Hata model predicted equal loss, although framed differently. We validated the adjusted Egli and Hata’s model with the original models and the FCC-based Perez Vega model using a coefficient of determination, which showed improved performance for the North and the South. This study will help in optimizing the existing path loss model using the least-square approximation method and obtain the optimal prediction model for the study area or other areas with similar topography. This will aid communication service enhancement, the proper planning, and the future deployment of wireless communication system across the study area.