Satellite networks are rapidly evolving, yet most \glspl{ntn} remain isolated from terrestrial orchestration frameworks. Their control architectures are typically monolithic and static, limiting their adaptability to dynamic traffic, topology changes, and mission requirements. These constraints lead to inefficient spectrum use and underutilized network capacity. Although \gls{ai} promises automation, its deployment in orbit is limited by computing, energy, and connectivity limitations. This paper introduces Space-O-RAN, a distributed control architecture that extends Open RAN principles into satellite constellations through hierarchical, closed-loop control. Lightweight \glspl{dapp} operate onboard satellites, enabling real-time functions like scheduling and beam steering without relying on persistent ground access. Cluster-level coordination is managed via \glspl{spaceric}, which leverage low-latency \glspl{isl} for autonomous decisions in orbit. Strategic tasks, including AI training and policy updates, are transferred to terrestrial platforms \glspl{smo} using digital twins and feeder links. A key enabler is the dynamic mapping of the O-RAN interfaces to satellite links, supporting adaptive signaling under varying conditions. Simulations using the Starlink topology validate the latency bounds that inform this architectural split, demonstrating both feasibility and scalability for autonomous satellite RAN operations.

翻译：卫星网络正在快速发展，然而大多数非地面网络（NTN）仍与地面编排框架相隔离。其控制架构通常是单体式且静态的，限制了其对动态流量、拓扑变化及任务需求的适应性。这些约束导致频谱使用效率低下和网络容量未充分利用。尽管人工智能（AI）有望实现自动化，但其在轨部署受限于计算能力、能源和连接性。本文提出Space-O-RAN，一种通过分层闭环控制将开放无线接入网（O-RAN）原则扩展至卫星星座的分布式控制架构。轻量级去中心化应用（dApp）在卫星上运行，可实现调度与波束赋形等实时功能，而无需依赖持续的地面接入。集群级协调通过空间无线接入网智能控制器（SpaceRIC）管理，其利用低延迟星间链路（ISL）在轨进行自主决策。包括AI训练和策略更新在内的战略性任务，则通过数字孪生和馈电链路转移至地面平台服务管理与编排器（SMO）。一个关键使能技术是将O-RAN接口动态映射至卫星链路，以支持变化条件下的自适应信令。基于星链（Starlink）拓扑的仿真验证了指导此架构划分的时延边界，证明了自主卫星无线接入网运营的可行性与可扩展性。