xSTART: xApp Simulated Evaluation Environment for Developers

The advent of the Open Radio Access Network (Open RAN) in 5G, as delineated in the standards introduced by 3GPP and O-RAN Alliance, posed a pivotal shift in revolutionizing the telecommunications landscape. Central to this transformation is the Open RAN control-plane architecture. Control plane encompasses containerized network functions, operating as intelligent controllers for RAN nodes and resources with non-Real-Time and near-Real-Time constraints. These functions, called Near Real-Time RAN Intelligent Controller (Near-RT RIC) and Non Real-Time RAN Intelligent Controller (Non-RT RIC), include operators-defined applications, respectively named xApps and rApps, serving as common cloud-native applications controlling and optimizing Open RAN elements. Understanding the entire development process and runtime behaviour for these applications becomes an essential prerequisite for providing support for next-generation networks. However, the lack of ready-to-use tools that allow developers to test and evaluate their applications in simulated and real environments makes it difficult to study and experiment with xApps. In this work, we propose xSTART, a ready-to-deploy environment based on Docker technology that allows xApp developers to quickly deploy and incorporate their xApps in a simulated ns-3 environment to test and evaluate their functionalities. Then, we evaluate an IIoT Network use-case scenario showing a machine learning (ML)-based xApp applied to the O-RAN environment. The results compare the use of different ML techniques and show the correct behavior of the simulation. Finally, we make xSTART available to the community to ease the development and evaluation of future xApps.