Abstruct

The 4th International Workshop on Intelligent Aerial and Spaceborne Systems for 6G (6G-SAGA) focuses on AI-native algorithms, digital-twin-enabled intelligence, and multi-orbit decision-making for emerging Non-Terrestrial Networks (NTN) in 6G. As NTNs integrate LEO/MEO/GEO satellites, HAPS/UAV platforms, and terrestrial infrastructure, new system-level challenges arise in predictive control, QoE/QoO aware orchestration, mobility continuity, spectrum coexistence, and service resilience. The above PHY topics fall outside the scope of the main IEEE GLOBECOM 2026 symposia, which emphasise PHY/MAC, MIMO, Reconfigurable Intelligent Surfaces (RIS), Integrated Sensing and Communications (ISAC), and satellite physical-layer techniques. This workshop invites contributions on learning-based routing, scheduling, mobility prediction, TN–NTN resource brokering, D2D (Direct to Device) NTN access, and digital twin-driven closed-loop optimisation. By bringing together researchers from academia, industry, and national labs, 6G-SAGA provides a timely venue for advancing intelligent, scalable, and efficient multi-orbit NTN solutions for 6G.

TOPICS

• AI-native multi-orbit resource allocation incorporating QoE and QoO decision metrics
• Learning-based scheduling and Doppler/latency prediction for highly dynamic NTN links
• RL and multi-agent RL algorithms for routing and mobility management in dense LEO constellations
• AI-enabled prediction and mitigation of LEO handover bursts for continuous user-perceived QoE
• QoO-optimized multi-orbit path selection and routing across LEO–MEO–GEO/HAPS systems
• ML models for feeder-link congestion forecasting and proactive load balancing
• DT modeling of traffic, mobility, and constellation dynamics for predictive NTN analysis
• Closed-loop optimization frameworks for real-time NTN orchestration
• Integrated TN–NTN DT environments for QoE-driven multi-access selection and coordination
• AI-native TN–NTN resource brokering, slicing, and service orchestration guided by QoE/QoO objectives
• Learning-driven spectrum sharing and interference coordination for TN–NTN coexistence (above PHY)
• AI-enhanced MAC-level access and session continuity for D2D NTN services
• AI-enabled anomaly detection, resilience, and self-healing mechanisms for robust multi-orbit NTN operations

IMPORTANT DATES

• Paper Submission: 12 August 2026
• Acceptance Notification: 20 September 2026
• Camera-Ready: 30 September 2026
• Workshop Date: 7 or 11 December 2026