This paper presents an extensible ns-3-based simulation framework for evaluating intent-based, semantics-aware control in Open RAN architectures. The framework integrates external Radio Access Network (RAN) Intelligent Controller (RIC) components and supports fine-grained control via internal distributed applications (dApps), enabling intent-based RAN orchestration across different timescales while maintaining standardized network behavior. As an illustrative use case, we implement an intent-based dApp for radio resource management (RRM) under realistic observability constraints. The scheduling problem is formulated using realistic key performance measurements (KPMs) available to dApps, together with a newly introduced Intent Satisfaction Score (ISS), which quantifies the delivery of intent-relevant information by combining distortion- and perception-oriented measures. Simulation results show that intent-based RRM can improve ISS while significantly reducing radio resource usage and computational overhead, at the cost of a moderate reduction in packet delivery ratio and throughput.

翻译：本文提出一种可扩展的基于ns-3的仿真框架，用于评估开放RAN架构中基于意图的语义感知控制。该框架集成了外部无线接入网（RAN）智能控制器（RIC）组件，并通过内部分布式应用（dApps）支持细粒度控制，从而能够在标准化网络行为下实现跨不同时间尺度的基于意图的RAN编排。作为示例应用场景，我们在实际可观测性约束下实现了一种用于无线电资源管理（RRM）的基于意图的dApp。调度问题利用dApps可获取的真实关键性能测量值（KPMs）进行建模，并引入新提出的意图满意度评分（ISS）——该评分通过结合失真导向与感知导向的度量指标来量化意图相关信息的传递效果。仿真结果表明，基于意图的RRM可在显著降低无线资源使用率与计算开销的同时提升ISS，但会适度牺牲分组投递率与吞吐量。