A Unified HAPS-LEO NTN Architecture for 6G: Enabling Hybrid RF-FSO Backhaul and Distributed Federated Learning
Authors:-Aakash Jain, Prakhar Vats, Priyanshu Singh, Shreya Tiwari. Mohammed Alim
Abstract-As communication systems evolve towards beyond-5G and 6G, the demand for high data rates, minimized latency, global connectivity, and distributed intelligence intensifies. Traditional terrestrial and backhaul networks face limitations in scalability, bandwidth, and coverage, particularly in challenging environments. This paper proposes a unified, multi-tier Non-Terrestrial Network (NTN) architecture integrating Low Earth Orbit (LEO) satellites and High Altitude Platform Stations (HAPS) to address these challenges. We explore a hybrid RF-Free-Space Optical (FSO) communication model to leverage the strengths of both technologies, enhancing backhaul efficiency and resilience against atmospheric disruptions. The architecture incorporates Contact Graph Routing (CGR) for optimized data routing in dynamic backhaul scenarios and a distributed Hierarchical Federated Learning (HFL) framework, utilizing HAPS as intermediate servers, to enable privacy-preserving, scalable machine learning across the network. This unified approach offers a versatile platform for future communication systems, supporting both high-performance backhaul and distributed intelligence. Simulated performance results, adapted from component studies, demonstrate the potential advantages of this integrated architecture in terms of latency, throughput, scalability, and learning accuracy.
