xDevSM: An Open-Source Framework for Portable, AI-Ready xApps Across Heterogeneous O-RAN Deployments
Angelo Feraudo, Stefano Maxenti, Andrea Lacava, Leonardo Bonati, Paolo Bellavista, Michele Polese, and Tommaso Melodia

TL;DR
xDevSM is an open-source framework that simplifies the development of AI-enabled xApps for heterogeneous O-RAN deployments by unifying observability and control, validated on real-world testbeds.
Contribution
It introduces a unified, developer-friendly framework that enhances interoperability and control in O-RAN, facilitating practical AI-driven xApp development across diverse hardware and software stacks.
Findings
Demonstrated seamless interoperability across multiple RAN hardware and software stacks.
Validated the framework on real-world testbeds with COTS devices and SDRs.
Showed the framework's capability to support advanced network control scenarios.
Abstract
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…
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Taxonomy
TopicsSoftware-Defined Networks and 5G · Cognitive Radio Networks and Spectrum Sensing · Advanced MIMO Systems Optimization
