AI-driven orchestration for integrated satellite-terrestrial 6G networks: Architecture, handover management, and testbed evaluation
The integration of terrestrial and Non-Terrestrial Networks (NTNs) is a cornerstone of the sixth-Generation (6G) vision, yet orchestrating artificial intelligence (AI) workloads across these heterogeneous domains remains an open challenge. This paper introduces an AI-driven orchestration architecture for integrated satellite-terrestrial 6G networks that extends four components of our previously proposed AI-native design, namely the 3rd Generation Partnership Project (3GPP) enhanced Network Data Analytics Function (NWDAF), Service Hosting Environment (SHE), Network Knowledge Exposure Function (NKEF), and AI agent framework, with NTN-specific capabilities. Drawing on a systematic analysis of the 20 ubiquitous connectivity use cases and the five AI-NTN convergence use cases from the 3GPP Technical Report (TR) 22.870 document, we conceptualize these architectural extensions: (i) an NTN-enhancement to NWDAF for ingesting satellite telemetry and ephemeris data to be used in predictive handover and coverage analytics, (ii) a space-edge computing tier within SHE that enables onboard satellite AI inference with a latency-aware model placement framework, (iii) a cross-domain AI agent for intent-driven orchestration across terrestrial and satellite operator boundaries, and (iv) an NKEF feature exposing constellation topology and coverage predictions to third-party applications. In order to demonstrate the effectiveness of this orchestration architecture, we present a handover management framework addressing four transition types (satellite-to-satellite, satellite-to-terrestrial hand-out, terrestrial-to-satellite hand-in, and inter-orbit) with backhaul-aware path selection leveraging inter-satellite links. Next, a comparative evaluation of eight NTN testbed platforms identifies current validation capabilities and gaps with respect to the discussed end-to-end system. [...]