Openness and programmability in the O-RAN architecture enable closed-loop control of the Radio Access Network (RAN). Artificial Intelligence (AI)-driven xApps, in the near-real-time RAN Intelligent Controller (RIC), can learn from network data, anticipate future conditions, and dynamically adapt radio configurations. However, their development and adoption are hindered by the complexity of low-level RAN control and monitoring message models exposed over the O-RAN E2 interface, limited interoperability across heterogeneous RAN software stacks, and the lack of developer-friendly frameworks. In this paper, we introduce xDevSM, a framework that significantly lowers the barrier to xApp development by unifying observability and control in O-RAN deployment. By exposing a rich set of Key Performance Measurements (KPMs) and enabling fine-grained radio resource management controls, xDevSM provides the essential foundation for practical AI-driven xApps. We validate xDevSM on real-world testbeds, leveraging Commercial Off-the-Shelf (COTS) devices together with heterogeneous RAN hardware, including Universal Software Radio Peripheral (USRP)-based Software-defined Radios (SDRs) and Foxconn radio units, and show its seamless interoperability across multiple open-source RAN software stacks. Furthermore, we discuss and evaluate the capabilities of our framework through three O-RAN-based scenarios of high interest: (i) KPM-based monitoring of network performance, (ii) slice-level Physical Resource Block (PRB) allocation control across multiple User Equipments (UEs) and slices, and (iii) mobility-aware handover control, showing that xDevSM can implement intelligent closed-loop applications, laying the groundwork for learning-based optimization in heterogeneous RAN deployments. xDevSM is open source and available as foundational tool for the research community.

翻译：O-RAN架构的开放性与可编程性实现了对无线接入网（RAN）的闭环控制。在近实时RAN智能控制器（RIC）中，由人工智能（AI）驱动的xApp能够从网络数据中学习、预测未来状态并动态调整无线配置。然而，其开发与应用面临以下阻碍：通过O-RAN E2接口开放的低层RAN控制与监测消息模型复杂度高，异构RAN软件栈间的互操作性有限，以及缺乏对开发者友好的框架。本文提出xDevSM框架，该框架通过统一O-RAN部署中的可观测性与控制能力，显著降低了xApp的开发门槛。通过开放丰富的关键性能指标（KPM）集合并支持细粒度无线资源管理控制，xDevSM为实际AI驱动的xApp提供了必要基础。我们在真实测试平台上验证了xDevSM，结合商用现成（COTS）设备与异构RAN硬件（包括基于通用软件无线电外设（USRP）的软件定义无线电（SDR）和富士康无线单元），并展示了其在多种开源RAN软件栈间的无缝互操作性。此外，我们通过三个备受关注的O-RAN应用场景对框架能力进行探讨与评估：（i）基于KPM的网络性能监测，（ii）跨多用户设备（UE）与切片的切片级物理资源块（PRB）分配控制，以及（iii）移动性感知的切换控制。实验表明xDevSM能够实现智能闭环应用，为异构RAN部署中基于学习的优化奠定基础。xDevSM已开源，可作为研究社区的基础工具使用。