Reliable Transmission Optimization for UAV-Relayed Space–Air–Ground Integrated Vehicular Networks

Abstract

Driven by the vision of sixth-generation (6G) communication networks, Space–Air–Ground Integrated Vehicular Networks (SAGVNs) address the connectivity blind spots inherent in traditional networks by integrating unmanned aerial vehicles (UAVs) as highly mobile relay nodes. However, the high bit error rates (BERs) and prolonged propagation delays characteristic of satellite links, coupled with the highly dynamic topologies and multi-hop transmission nature of UAVs and terrestrial vehicles, present significant challenges to reliable end-to-end data streaming. To mitigate the performance degradation caused by link asymmetries in heterogeneous networks, this paper proposes a reliable transmission optimization scheme for UAV-relayed SAGVNs. By comprehensively modeling the transmission dynamics of long-delay, high-BER satellite links and mobile multi-hop UAV networks, the proposed scheme introduces an enhanced slow-start mechanism to accelerate throughput growth, thereby mitigating the startup lag induced by extensive propagation delays. Furthermore, an accurate packet loss differentiation model is established during the congestion avoidance phase. This model effectively decouples non-congestion packet losses—triggered by random channel errors or topology handovers due to high-speed node mobility—from genuine congestion-induced losses caused by buffer overflows at bottleneck nodes. Simulation results demonstrate that the proposed adaptive scheme demonstrates notable improvements over classical loss-based and delay-based baselines in reducing queuing delays at UAV relay nodes, enhances the transmission efficiency of multi-hop terminals, and effectively maintains end-to-end goodput stability in high-latency environments.