  Over the past few decades, the development of cellular communication
technology has spanned several generations in order to add sophisticated
features in the updated versions. Moreover, different high-frequency bands are
considered for advanced cellular generations. The presence of updated
generations like 4G and 5G is driven by the rising demand for a greater data
rate and a better experience for end users. However, because 5G-NR operates at
a high frequency and has significant propagation, atmospheric fluctuations like
temperature, humidity, and rain rate might result in poorer signal reception,
and higher path loss effects unlike the prior generation, which employed
frequencies below 6 GHz. This paper makes an attempt to provide a comparative
analysis about the influence of different relative atmospheric conditions on 5G
cellular communication for various operating frequencies in any urban microcell
(UMi) environment maintaining the real outdoor propagation conditions. In
addition, the simulation dataset based on environmental factors has been
validated by the prediction of path loss using multiple regression techniques.
Consequently, this study also aims to address the performance analysis of
regression techniques for stable estimations of path loss at high frequencies
for different atmospheric conditions for 5G mobile generations due to various
possible radio link quality issues and fluctuations in different seasons in
South Asia. Furthermore, in comparison to contemporary studies, the Machine
Learning models have outperformed in predicting the path loss for the four
seasons in South Asian regions.
