Calibration and Automation of a 5G Simulator for Realistic Evaluation and Data Generation

Conrado Boeira, Antor Hasan, Khaleda Papry, Yue Ju, Zhongwen Zhu, Israat Haque

Abstract: The rise of 5G deployments has created the environment for many emerging technologies to flourish. Self-driving vehicles, Augmented and Virtual Reality, and Remote Surgery are examples of applications that leverage 5G networks’ support for extremely low latency, high bandwidth, and increased throughput. However, the complex architecture of 5G hinders innovation due to the lack of accessibility to testbeds or realistic simulators with adequate 5G functionalities. Also, configuring and managing simulators are complex and time consuming. Finally, the lack of adequate representative data hinders the data-driven designs in 5G campaigns. Thus, we calibrated a system-level open-source simulator, Simu5G, following 3GPP guidelines to enable faster innovation in the 5G domain. Furthermore, we developed an API for automatic simulator configuration without knowing the underlying architectural details. Thus, researchers can use the calibrated and automated simulation to test various 5G functionalities and generate realistic operational data for data-driven designs.