AI-Native Open RAN for Non-Terrestrial Networks: An Overview

TL;DR

This paper provides a comprehensive overview of integrating AI-Native ORAN frameworks into Non-Terrestrial Networks to address mobility and resilience challenges in 6G, highlighting technological enablers and future research directions.

Contribution

It introduces a structured framework for AI-Native ORAN-based NTN, filling a gap in holistic understanding and practical implementation strategies for 6G networks.

Findings

Proposed an orchestrated AI-Native ORAN framework for NTN

Identified key technological enablers for AI integration in NTN

Outlined future research directions for AI-Native NTN

Abstract

Non-terrestrial network (NTN) is envisioned as a critical component of Sixth Generation (6G) networks by enabling ubiquitous services and enhancing network resilience. However, the inherent mobility and high-altitude operation of NTN pose significant challenges throughout the development and operations (DevOps) lifecycle. To address these challenges, integrating NTNs with the Open Radio Access Network (ORAN) is a promising approach, since ORAN can offer disaggregation, openness, virtualization, and embedded intelligence. Despite extensive literature on ORAN and NTN, a holistic view of ORAN-based NTN frameworks is still lacking, particularly regarding how ORAN can effectively address the existing challenges of NTN. Furthermore, although artificial intelligence native (AI-Native) capabilities have the potential to enhance intelligence network control and optimization, their practical realization in NTNs has not yet been sufficiently investigated. Therefore, in this paper, we provide a comprehensive and structured overview of AI-Native ORAN for NTN. This paper commences with an in-depth review of the existing literature and subsequently introduces the necessary background about ORAN, NTN, and AI-Native for communication. After analyzing the DevOps challenges for NTN, we propose the orchestrated AI-Native ORAN-based NTN framework and discuss its key technological enablers. Finally, we present the representative use cases and outline the prospective future research directions of this study.