| 6G-INTEGRATION-3-E5 |
Innovations for the NTN integration with 3GPP networks |
This document reviews the fundamentals of satellite communications and the latest advances in fault-tolerant onboard equipment, AI/ML-based applications in STIN, and advancements and deployments in Non-Terrestrial Networks (NTNs). Additionally, the document delves into the 3GPP Release 17 standard in the context of NTN and analyzes the state of the art in hardware fault tolerance strategies in the space segment, as well as the applications of AI/ML in optimizing the operation and performance of satellite communications and High-Altitude Pseudo-Satellites (HAPS). Finally, the document concludes with a brief summary
of the contributions and the analyzed state of the art. |
| 6G-INTEGRATION-3-E6 |
Enhanced innovations for the NTN integration with 3GPP networks |
This document provides a summary of examples for enhanced innovations in the NTN integration with 3GPP networks. The main innovations overviewed have to do with the applicability of modern AI/ML algorithms to help modeling, solving and optimizing different aspects of NTNs built with both terrestrial equipment and on-air and space equipment. Main challenges in these types of networks have to do with dealing with high latency, the errors due to radiation and transmission impairments, Doppler shifts, mobility management, handovers between terrestrial and non-terrestrial networks, channel reliability. Multi-access Edge Computing (MEC) can provide caching and computing resources on board to provide near real-time applications to minimise latency. Also intelligent algorithms based on Reinforcement Learning and other AI/ML strategies can be used to optimise network performance from multiple sides: resource optimization, optimal routing, network slicing and mobility management. This document provides an overview of such strategies and algorithms toward a real integration of both terrestrial and non-terrestrial networks with current 5G deployments and emerging 6G networks. |
