Modeling Tropospheric Effects on Mobile Network Performance Using KPI-Based Metrics

Abstract

Understanding how tropospheric variability influences mobile communication systems is critical for improving network reliability. This need is especially important in regions characterized by rapid atmospheric fluctuations. This study presents a quantitative modeling framework for evaluating tropospheric effects on mobile network performance using key performance indicators (KPIs). Tropospheric parameters including temperature, relative humidity, atmospheric pressure, and wind conditions were synchronized with corresponding network KPIs. These include Call Setup Success Rate (CSSR), Traffic Channel Congestion Rate (TCHCR), Handover Success Rate (HOSR), and Received Signal Strength. Statistical techniques comprising Pearson correlation, multiple regression modeling, and hypothesis testing were employed. These methods were used to determine the magnitude, direction, and significance of atmospheric influences. Results reveal that temperature and humidity exhibit strong, statistically significant associations with signal strength and call reliability. Pressure and wind parameters show moderate but noteworthy effects on congestion and handover performance. The developed models demonstrate that tropospheric conditions account for a substantial proportion of KPI variability. This indicates that atmospheric impairments play a measurable role in network degradation. The study provides a data-driven basis for proactive network optimization. It enables operators to incorporate atmospheric behaviors into predictive maintenance, link budgeting, and adaptive radio-resource management. The findings contribute to an improved understanding of environmental impacts on mobile communication systems. They also support the design of more resilient networks under dynamic tropospheric conditions.