Radio Channel Predicted Model of Deployed Cellular Network in Algiers City

The study of the radio environment characteristics is necessary to enhance the precision of the cellular network mobile station localization. In this work, we use a linear regression technique based on the ordinary least squares approach to illustrate a radio channel model customized for the cellular network radio environment of Algiers, Algeria. We use the Log-normal, K-factor, and Okumura-Hata models. Real RSSI measurements were made on a deployed cellular network with the aid of special software made for this purpose. The generated findings can be verified by computing the square root of the mean square error between the real data, the radio measurements, and the predicted data created from the used model. The new model could improve the efficiency of the cellular network radio systems deployed in Algiers.