开源5G无线接入网（RAN）平台：性能与能力的双视角研究
Open-Source 5G RAN Platforms: A Dual Perspective on Performance and Capabilities
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中文总结 AI 辅助
本文对比评估开源5G RAN平台OAI与srsRAN，通过定性分析功能与部署灵活性、定量分析含VoD、LS、CG的性能，填补了多维度评估的研究空白。
中文摘要 AI 辅助
第五代（5G）无线接入网（RAN）的开源实现，如OpenAirInterface（OAI）和srsRAN，在工业界、学术研究、快速原型开发以及低成本私有5G部署中愈发重要。现有研究针对这两个平台的评估场景各异，但往往局限于单个测试床评估、端到端研究或二者间的部分比较，尤其缺乏考虑不同软件定义无线电（SDR）、RAN配置、用户应用及真实用户设备（UE）数量的评估。为填补这一空白，本文对OAI和srsRAN开展对比评估，包含对支持功能与部署灵活性的定性评估，以及覆盖无线资源控制建立流程、理论数据速率合规性、具备不同服务质量要求的真实应用负载的定量性能分析。具体而言，本文将视频点播（VoD）用于数据速率评估，将直播流（LS）和云游戏（CG）作为对延迟敏感的应用，这些负载全面呈现了各平台的能力。
英文摘要
Open-source implementations of the fifth generation (5G) Radio Access Network (RAN), such as OpenAirInterface (OAI) and srsRAN, have become increasingly relevant for industry and academic research, rapid prototyping, and low-cost private 5G deployments. The state of the art presents different evaluation scenarios for both platforms; however, these are often limited to individual testbed evaluations, end-to-end studies, or partial comparisons between them. In particular, there is a lack of evaluations considering different Software-Defined Radios (SDRs), RAN configurations, user applications, and numbers of real UEs. To address this gap, this paper presents a comparative evaluation of OAI and srsRAN. The study includes a qualitative assessment of supported features and deployment flexibility, followed by a quantitative performance analysis covering radio resource control setup procedures, compliance with theoretical data rates, and real application workloads with diverse quality of service requirements. Specifically, we consider Video on Demand (VoD) for data rate evaluation, Live Streaming (LS) and Cloud Gaming (CG) as latency-sensitive applications. These workloads provide a comprehensive view of each platform capability.
