Automated Drive-Test System for Mobile Communication Networks

The technological advancement referred to as Industry 4.0 is directly linked to the evolution of telecommunications. A prominent example of this relationship is the emergence of fifth-generation mobile communication standards, commonly known as 5G, which have enabled the industrial application of disruptive technologies such as artificial intelligence, augmented reality, big data, IoT, among others, in an increasingly scalable manner. In light of this scenario, it is of utmost importance that solutions for analyzing and monitoring the performance of mobile networks become more accessible, not relying solely on high-cost equipment, proprietary software, or applications limited to networks compatible with smartphones. In this context, the main objective of this work was to develop an automated drive-test system for mobile communication networks, capable of generating georeferenced heat maps that represent the received signal strength through the RSRP (Reference Signal Received Power) parameter in performance tests conducted in a specific operational area of a mobile network. It is important to highlight that the validation of the current system functionalities was conducted on a private 5G network, thanks to the infrastructure provided by Itaipu Parquetec, which generously authorized the validation tests within its coverage area. However, the system was designed to be adaptable to other types of mobile network technologies, depending only on the possibility of integration between the developed system and the devices connected to the network to be analyzed. The system architecture was defined to encompass the following layers: data acquisition, where a 5G development kit and a georeferencing module were used integrated with a computational data acquisition interface; data layer, consisting of a non-relational database; application layer, composed of a server implemented with FastAPI, React, Node.js, Bootstrap, and Leaflet; and finally, a presentation layer that should be displayed in a web browser. After comparative analysis between the tests conducted, an approximate reduction of 89% in test execution time was observed when using the developed automated drive-test system compared to the manual method, highlighting the significant potential of this tool.