Non-Terrestrial Integrated Access and Backhaul for 6G LEO Satellite MVNO
The developed system will be tested and validated on the state-of-the-art federated learning and network slicing testbed at NC State University.
This project seeks to create AI-based federated slicing and orchestration for managing constellation networks and providing AI/real-time services. The proposed designs will optimize the resources and networking configurations of ground and space tiers, as well as multiple constellations, to create high-throughput, reliable end-to-end transmissions. These designs will be tested and validated on the federated learning and network slicing testbed at NC State.
Cisco Systems, Inc.
The grant—running from February 16, 2023 to February 15, 2024—is for a total of $178,972.
This project aims to develop AI-native federated slicing and orchestration that enables the synergy of federated AI and network slicing for mega-constellation management and AI/real-time services. A federated edge learning setting facilitates multi-tier, multi-domain AI executions by jointly optimizing resource and networking configurations of ground and space tiers and multiple constellations. Hence, the proposed designs will create high-throughput, reliable end-to-end transmissions for global connectivity.