用AI和开放架构构建面向空天网络的统一无线接入网
AI-Open-RAN for Non-Terrestrial Networks
- 基于开放接口与AI功能，整合AIO-RAN与3GPP标准
- 实验显示低速移动下性能敏感，但AI可精准预测关键指标
- 适合5G空天网络研发者与系统架构师参考
本文提出AIO-RAN-NTN概念，一种面向非地面网络（NTNs）的统一全功能无线接入网，采用开放架构并融合开放接口与人工智能（AI）功能。该设计提升了下一代通信系统的互操作性、灵活性与智能化水平。首先，综述了Open-RAN与AI-RAN的最新架构，突出关键网络功能与基础设施要素。随后，提出集成式AIO-RAN-NTN蓝图，说明AIO-RAN内部及空中接口如何适配如NTNs等新兴场景。为评估移动性影响，使用OpenAirInterface平台搭建独立（SA）NR 5G系统测试床进行传输实验，并基于真实数据训练AI模型以预测关键性能指标（KPI）。实验表明，基于AIO的SA架构在低速移动下仍具敏感性，但可通过AI驱动的KPI预测有效缓解此问题。
原文摘要 · Abstract (English)
In this paper, we propose the concept of AIO-RAN-NTN, a unified all-in-one Radio Access Network (RAN) for Non-Terrestrial Networks (NTNs), built on an open architecture that leverages open interfaces and artificial intelligence (AI)-based functionalities. This approach advances interoperability, flexibility, and intelligence in next-generation telecommunications. First, we provide a concise overview of the state-of-the-art architectures for Open-RAN and AI-RAN, highlighting key network functions and infrastructure elements. Next, we introduce our integrated AIO-RAN-NTN blueprint, emphasizing how internal and air interfaces from AIO-RAN and the 3rd Generation Partnership Project (3GPP) can be applied to emerging environments such as NTNs. To examine the impact of mobility on AIO-RAN, we implement a testbed transmission using the OpenAirInterface platform for a standalone (SA) New Radio (NR) 5G system. We then train an AI model on realistic data to forecast key performance indicators (KPIs). Our experiments demonstrate that the AIO-based SA architecture is sensitive to mobility, even at low speeds, but this limitation can be mitigated through AI-driven KPI forecasting.
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