Artificial Intelligence in Open Radio Access Network

TL;DR

This paper discusses the deployment of Open Radio Access Network (O-RAN) for 5G, emphasizing AI/ML integration for improved management, flexibility, and security, replacing hardware-specific components with open, software-based solutions.

Contribution

It highlights the role of AI/ML in O-RAN management and explores future security challenges in 5G networks.

Findings

AI/ML enables faster RAN analytics and management.

Open software-based RAN reduces reliance on specific manufacturers.

Security concerns are critical for future O-RAN deployment.

Abstract

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.