Abstract

The aim of this proposed technique is to optimize the prediction quality and to minimize the overall measured RMSE error of the original Lee’s path loss model. The new technique is a statistical algorithm based on the concept of mean value normalization that has a wide range of applications. Statistical path loss models, such as Lee’s model, are assumed as major prediction models used primarily in the pre-planning procedures to pre-estimate losses and minimize the overall cost. Lee’s model as a major prediction model is well known to accurately predict such losses in diverse landscape criteria’s. As compared to the original model, the new proposed technique has demonstrated better RMSE accuracy. Less RMSE, of an average of 3-4 dB’s is obtained in most macro-cell open areas in the area of Jiza town, south of Amman city, Jordan. Examples are provided in both the 900 MHz and the 1800 MHz to signify the enhancement of the prediction accuracy of the new proposed algorithm.

Keywords:

Large scale path loss models , model optimization , statistical parameters,

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Competing interests

The authors have no competing interests.

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