A Comparative and Measurement-Based Study on Real-Time Network KPI Extraction Methods for 5G and Beyond Applications

Abstract

Key performance indicators (KPIs), which can be extracted from the standardized interfaces of network equipment defined by current standards, constitute a primary data source that can be leveraged in the development of non-standardized new equipment, architectures, and computational tools. In next-generation technologies, the demand for data has evolved beyond the conventional log generation or export capabilities provided by existing licensed network monitoring tools. There is now a growing need to collect such data at specific time intervals and with defined granularities. At this stage, the development of real-time KPI extraction methods and enabling their exchange between both standardized/commercialized and non-standardized components or tools has become increasingly critical. This study presents a comprehensive evaluation of three distinct KPI extraction methodologies applied to two commercially available devices. The analysis aims to uncover the strengths, weaknesses, and overall efficacy of these approaches under varying conditions, and highlights the critical insights into the practical capabilities and limitations. The findings serve as a foundational guide for the seamless integration and robust testing of novel technologies and approaches within commercial telecommunication networks. This work aspires to bridge the gap between technological innovation and real-world applicability, fostering enhanced decision-making in network deployment and optimization.