A simulation framework for mobility use case oriented RAN dataset generation

Guaranteeing sustainable QoS (Quality of Service) for the connected devices and services that will compose the Sixth Generation (6G) ecosystem still dominates the discourse given their resource and latency requirements. In Vehicle-To-Everything networks (V2X), requisite for the Qos sustainability is localization and directional metrics about the individual entities as such measurements aid the network operator in system parameter re-calibration to meet expected Service Level Agreements (SLAs). With finer granularity to the cell level, Third Generation Partnership Project (3GPP) suggests for the abstraction of these metrics in the Location Management Function (LMF) of the network core to underpin analytics processes in the Network Data Analytics Function (NWDAF). For further development and evaluation of these processes, be it in the Radio Access Network (RAN) or core, experimental tooling is needed. Our work introduces custom functionality that integrates Network Simulator-3 (ns-3) with Simulation of Urban MObility (SUMO) to retrieve localization and directional information combined with throughput and connectivity measures. The new features enable the generation of datasets that can find use in the development of Machine Learning (ML) algorithms for trajectory oriented resource allocation in V2X systems.