Jun 2026· ITU Journal on Future and Evolving Technologies· Vol 7, pp. 188-212· 1 citation
TL;DR
An AI-driven orchestration architecture for integrated satellite-terrestrial 6G networks that extends four components of the 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 are introduced.
Abstract
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. [...]
Intent-Based Networking (IBN) has emerged as a promising paradigm for simplifying network management by allowing operators and applications to specify high-level service objectives rather than low-level device configurations. Early IBN research was mainly developed in Software-Defined Networking (SDN), Network Function Virtualization (NFV), transport networks, core networks, and data-center environments, where programmability, virtualization, and relatively stable infrastructure models enabled intent translation, orchestration, and assurance. However, realizing IBN in end-to-end mobile networks is more challenging because the Radio Access Network (RAN) is highly dynamic, wireless-channeldependent, mobility-sensitive, and governed by multiple control timescales. The emergence of Open RAN (O-RAN) changes this landscape by making the RAN programmable, disaggregated, data-driven, and control-lable through non-real-time and near-real-time intelligent control loops. This survey reviews the evolution of IBN from SDN/NFV-enabled automation toward O-RAN-driven end-to-end intent-based networking for 5G-Advanced and 6G. We discuss architectural mechanisms, key challenges, recent advances in AI-driven and agentic IBN, and future research directions including Large Language Model (LLM)-based intent translation, contractbased O-RAN slicing, digital twin-assisted validation, and trustworthy closed-loop orchestration.
Dongwook Won, Thanh Thien-An Dang, Ton That Tam Dinh et al.· International Conference on...· 0 citations
6G targets ultra-wide coverage together with ultra-low-latency and ultra-reliable services. To this end, Space-Air-Ground Integrated Networks (SAGINs), which integrate non-terrestrial networks (NTNs) with terrestrial networks (TNs), have emerged as a key candidate architecture. However, legacy resource management methods designed for terrestrial systems are difficult to apply directly due to high mobility and long propagation delays (and Doppler effects) of satellite/aerial platforms, dynamic topologies, and constrained onboard resources. In addition, under short-packet transmission (finite blocklength) regimes, QoS analysis must go beyond average-rate metrics and explicitly ensure latency and reliability simultaneously. This paper surveys resource management for SAGIN/TN-NTN integration through a three-axis taxonomy: (i) resource allocation/scheduling, (ii) mobility/dynamics, and (iii) statistical multi-QoS (latency-reliability) modeling. We compare representative works spanning optimization, graph deep reinforcement learning (Graph DRL), and finite-blocklength-based analyses. We also summarize virtualization/slicing and security/robustness as cross-cutting constraints, and highlight open research challenges.
Minjae Go, Woongsoo Na· International Conference on...· 0 citations
Efficient long-term network evolution is becoming increasingly critical in dense 5G-Advanced and beyond cellular systems, where persistent traffic imbalances and localized congestion pose significant challenges that conventional short-term radio resource management alone cannot fully mitigate. This paper proposes a digital twin (DT)-enabled non-real-time (NRT) network evolution framework integrated with a large language model (LLM). Within this architecture, the digital twin provides a high-fidelity, controllable environment for evaluating infrastructure actions, while the LLM serves as a strategic orchestration engine that recommends cost-efficient network upgrades based on observed network states. Unlike traditional optimization methods that require exhaustive mathematical reformulations for each specific scenario, the proposed framework leverages the reasoning capabilities of LLMs to interpret operator objectives and constraints in natural language, generating structured evolution plans. The considered NRT action space encompasses antenna upgrades, bandwidth expansion, and new base station (BS) deployment. A techno-economic formulation is introduced to jointly evaluate load reduction performance and overall economic expenditure. Numerical results in a dense cellular scenario demonstrate that the framework effectively reduces peak resource utilization and provides diverse, coordinated evolution strategies tailored to varying network conditions.
Yukai Wang, Janghee Woo, G. Hahm et al.· International Conference on...· 0 citations
CIS-RAN is proposed, a novel 6G RAN architecture built on three pillars of cooperative, intelligent, and service-based design that enables flexible collaboration across distributed RAN nodes and multi-dimensional domains, integrates intelligence throughout the network, and supports advanced RAN capability exposure as services.
Xiaoyun Wang, Nan Li, Qi Sun et al.· Science China Information Sc...· 0 citations
The telecommunication industry in India is undergoing a structural change, with the deployment of the 5G network, the widespread deployment of smart devices for the Digital India initiative and the need for ultra-low latencies, high-speed services for smart cities, healthcare, agriculture and industrial automation. Traditional network management methods, which are mostly based on static configuration and human intervention are increasingly proving to be insufficient for the scale, diversity and dynamism of these networks. This paper introduces an Artificial Intelligence (AI) centric network management framework that combines 5G radio access and core capabilities, Software-Defined Networking (SDN) for centralized and programmable control and Multi-access Edge Computing (MEC) for localized and low latency processing. This framework includes a traffic prediction module (based on Long Short-Term Memory (LSTM)) and a resource orchestration engine (Deep Q-Network (DQN)), both of which allow for closed-loop self-optimizing network actions. Mininet-WiFi and Ryu SDN controller were used to simulate a representative Indian metropolitan network topology and assess the proposed framework in comparison to a baseline configuration with conventional SDN. Experimental results show significant gains in end-to-end latency (53.3 %), throughput (53.2 %), jitter (60.7 %), packet loss (72.4 %) and resource-utilization efficiency (42.6 %). The results indicate that 5G-SDN-edge continuum orchestration can positively impact the Quality of Service (QoS) in India-specific use cases such as dense urban areas and rural areas with limited infrastructure. The paper also elaborates the deployment challenges pertinent to the Indian context like spectrum availability, fiber backhaul penetration, cost of edge infrastructure, and regulatory considerations, while proposing the directions for future research like federated learning in orchestrating with privacy constraints and upcoming 6G research initiatives.
Praveen Kumar, S. Hashmi, Preeti Singhwal et al.· International journal of com...· 0 citations
The integration of terrestrial and non-terrestrial networks is a key enabler for seamless global connectivity in 6G systems. Existing simulation tools typically address only one domain, lacking unified architectures for capturing transient protocol-level behavior during satellite mobility events. This paper introduces BrightLight, a hybrid emulation–simulation testbed for space–terrestrial integrated networks (STINs) that combines Linux network namespaces, NS-3 mmWave channel modeling, and an Open5GS core to execute real protocol stacks under configurable satellite mobility and gateway impairments. To demonstrate the platform's ability to capture fine-grained handover dynamics, we evaluate backhaul-aware handover over a Starlink-based constellation topology, comparing conventional satellite switching against inter-satellite link (ISL) assisted rerouting under ground-segment congestion. BrightLight successfully captures transient throughput evolution, TCP buffer drainage effects, and RTT dynamics throughout the handover process, revealing that routing via ISLs to uncongested ground stations substantially reduces latency and eliminates throughput degradation. These results validate BrightLight as an effective platform for studying protocol-level handover behavior in 6G STIN architectures.
Murat Parlakisik, Ertan Ozturk· International Mediterranean...· 0 citations