AI-Native Open RAN for Non-Terrestrial Networks: An Overview
This work addresses network management challenges for NTN in 6G, but it is incremental as it synthesizes existing concepts into a framework without presenting new experimental results.
This paper tackles the challenge of integrating AI-native capabilities into Non-Terrestrial Networks (NTN) for 6G by proposing an Open RAN (ORAN)-based framework to address scalability and intelligent orchestration issues, providing a comprehensive overview and analysis of the integration.
Non-terrestrial network (NTN) is expected to be a critical component of Sixth Generation (6G) networks, providing ubiquitous services and enhancing the system resilience. However, the high-altitude operation and inherent mobility of NTN introduce significant challenges across the development and operations (DevOps) lifecycle. Apart from that, how to achieve artificial intelligence native (AI-Native) capabilities in NTN for intelligent network management and orchestration remains an important challenge. To solve the challenges above, we propose integrating the Open Radio Access Network (ORAN) with NTN as a promising solution, leveraging its principles of disaggregation, openness, virtualization, and embedded intelligence. Despite extensive technical literature on ORAN and NTN, respectively, there is a lack of a holistic view of the integration of ORAN and NTN architectures, particularly in terms of how intelligent ORAN can address the scalability challenge in NTN management. To address this gap, this paper provides a comprehensive and structured overview of an AI-native ORAN-based NTN framework to support dynamic configuration, scalability, and intelligent orchestration. The paper commences with an in-depth review of the existing literature from leading industry and academic institutions, subsequently providing the necessary background knowledge related to ORAN, NTN, and AI-Native for communication. Furthermore, the paper analyzes the unique DevOps challenges for NTN and proposes the orchestrated AI-Native ORAN-based NTN framework, with a detailed discussion on the key technological enablers within the framework. Finally, this paper presents various use cases and outlines the prospective research directions of this study in detail.