开放无线接入网中的人工智能
Artificial Intelligence in Open Radio Access Network
AI总结：
该教程概述面向5G的O-RAN架构，说明软件化、开放接口及AI/ML融入RAN管理的作用，并讨论其在降低厂商依赖与设备安全方面的意义。
摘要：
本教程旨在概述面向第五代（5G）无线网络所提出的开放无线接入网（O-RAN）部署。O-RAN力求用通用硬件、专用软件和开放信令接口取代依赖特定硬件的无线接入网（RAN）组件，例如移动性管理实体（MME）或基站（gNB）。5G的虚拟化和网络切片特性使软件能够替代以往由专用硬件实现的功能。软件还可提供更快的分析，从而支持5G的时延要求和高级使用场景，即增强型移动宽带（eMBB）、大规模机器类型通信（mMTC）以及超可靠低时延通信（uRLLC）。此外，随着软件接管RAN的控制，将人工智能/机器学习（AI/ML）算法集成到RAN管理（尤其是用户平面）中成为可能。这种集成正是O-RAN的目标之一。最后，依托通用硬件以及专用的开源软件，可消除对特定设备制造商的依赖。本文将提出有关O-RAN未来的问题，并重点关注5G网络设备安全。
英文摘要：
This tutorial seeks to outline the proposed Open Radio Access Network (O-RAN) deployment for Fifth generation (5G) wireless networks. O-RAN seeks to supplant hardware-specific Radio Access Network (RAN) components (e.g., the mobility management entity (MME) or base station (gNB)) with generic hardware, specialized software, and open signaling interfaces. The virtualization and network slicing features of 5G allow for software to replace previously hardware specific functions. Software further provides faster analytics, thus supporting 5Gs latency requirements and advanced usage scenarios (i.e., enhanced mobile broadband (eMBB), massive machine type communications (mMTC), and ultra-reliable low latency communications (uRLLC)). Furthermore, as software annexes control of the RAN, there is freedom to integrate Artificial Intelligence/Machine Learning (AI/ML) algorithms into RAN management (particularly at the user plane). This integration is one of the goals of O-RAN. Lastly, relying on generic hardware and specialized, open-source software eliminates reliance upon specific device manufacturers. This paper will provide questions regarding the future of O-RAN, with a focus on 5G network device security.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
