Intelligent System for Integration in 5G Networks

This study investigates the performance and resilience of 5 G networks through an experimental setup based on 3GPP standards, employing Open5GS and srsRAN software. A baseline for normal network operations was established, with key metrics including channel quality indicators (CQI) and bitrates, followed by the introduction of controlled jamming to assess network disruptions. The network’s response to these disruptions was analyzed using a Random Forest (RF) algorithm, which demonstrated perfect accuracy in distinguishing between normal and jamming states. The results underscore the potential of 5 G technology in applications requiring low latency and high reliability, such as autonomous vehicles and remote surgeries. Furthermore, the study explores security implications and future advancements in edge computing and network slicing, contributing to a deeper understanding of 5G networks’ capabilities and vulnerabilities.