An In-Depth Survey on Virtualization Technologies in 6G Integrated Terrestrial and Non-Terrestrial Networks

TL;DR

This survey analyzes how Software-Defined Networking, Network Function Virtualization, and network slicing can virtualize and integrate 6G's terrestrial, aerial, and non-terrestrial networks (TN-NTNs). It emphasizes the role of AI in optimizing virtualization across SDN, NFV, and slicing, and introduces a four-level taxonomy to organize the literature. The authors review NTN characteristics, SAGIN architectures, key virtualization challenges, and concrete architectural and implementation contributions across S-T, A-T, and S-A-T segments, including simulation tools and testbeds. They identify open issues such as mobility, multi-domain orchestration, security, and the need for dedicated NTN-specific simulation tools, while highlighting emerging technologies like digital twins, blockchain, and quantum communications as enabling avenues.

Abstract

6G networks are envisioned to deliver a large diversity of applications and meet stringent quality of service (QoS) requirements. Hence, integrated terrestrial and non-terrestrial networks (TN-NTNs) are anticipated to be key enabling technologies. However, the TN-NTNs integration faces a number of challenges that could be addressed through network virtualization technologies such as Software-Defined Networking (SDN), Network Function Virtualization (NFV) and network slicing. In this survey, we provide a comprehensive review on the adaptation of these networking paradigms in 6G networks. We begin with a brief overview on NTNs and virtualization techniques. Then, we highlight the integral role of Artificial Intelligence in improving network virtualization by summarizing major research areas where AI models are applied. Building on this foundation, the survey identifies the main issues arising from the adaptation of SDN, NFV, and network slicing in integrated TN-NTNs, and proposes a taxonomy of integrated TN-NTNs virtualization offering a thorough review of relevant contributions. The taxonomy is built on a four-level classification indicating for each study the level of TN-NTNs integration, the used virtualization technology, the addressed problem, the type of the study and the proposed solution, which can be based on conventional or AI-enabled methods. Moreover, we present a summary on the simulation tools commonly used in the testing and validation of such networks. Finally, we discuss open issues and give insights on future research directions for the advancement of integrated TN-NTNs virtualization in the 6G era.

Figures (7)

• Figure 1: Survey Structure.
• Figure 2: Different roles of NTN platforms in integrated TN-NTN.
• Figure 3: Illustration of SDN architecture.
• Figure 4: Illustration of NFV architecture ETSI_NFV.
• Figure 5: Illustration of network slicing architecture by NGMN alliance2016description.