The Open Radio Access Network (O-RAN) architecture is reshaping the telecommunications landscape by enhancing network flexibility, openness, and intelligence. This paper establishes the requirements, evaluates the design tradeoffs, and introduces a scalable architecture and prototype of an open-source O-RAN experimentation platform within the Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW), an at scale testbed that integrates unmanned aerial vehicles (UAVs) with advanced wireless network technologies, offering experimentation in both outdoor testbed and emulation via a custom digital twin (DT). Through a series of aerial experiments, we evaluate FlexRIC, an open-source RAN Intelligent Controller, within the AERPAW hardware-software platform for network data monitoring, providing valuable insights into the proposed integration and revealing opportunities for leveraging O-RAN to create custom service based optimizations for cellular connected UAVs. We discuss the challenges and potential use cases of this integration and demonstrate the use of a generative artificial intelligence model for generating realistic data based on collected real-world data to support AERPAW's DT.

翻译：开放式无线接入网络（O-RAN）架构正通过提升网络灵活性、开放性与智能化，重塑电信行业格局。本文在AERPAW（先进无线空中实验与研究平台）这一将无人机与先进无线网络技术集成的大规模试验平台内，建立了开源O-RAN实验平台的需求规范，评估了设计权衡，并提出了一种可扩展的架构与原型。该平台支持通过定制数字孪生技术实现室外试验场与仿真环境双模式实验。通过一系列空中实验，我们在AERPAW软硬件平台内评估了开源无线接入网络智能控制器FlexRIC的网络数据监测性能，为所提出的集成方案提供了重要见解，并揭示了利用O-RAN为蜂窝网络连接无人机创建定制化服务优化方案的潜力。本文讨论了该集成面临的挑战与潜在应用场景，并演示了如何运用生成式人工智能模型基于采集的真实世界数据生成仿真数据，以支持AERPAW数字孪生系统的构建。