Holistic End-to-End Congestion Control for SAGIN-Integrated UAV Networks with Seamless Aerial-Terrestrial Integration

Area of Science:

• Network Engineering
• Telecommunications
• Aerospace Engineering

Background:

• Space-Air-Ground Integrated Networks (SAGINs) face performance bottlenecks due to satellite link latency and high bit error rates (BER).
• Unmanned Aerial Vehicle (UAV) networks introduce dynamic topologies and multi-hop communication challenges.
• Heterogeneous convergence of SAGIN and UAV networks requires specialized transport performance solutions.

Purpose of the Study:

• To propose a SAGIN-enabled Adaptive End-to-End Congestion Control scheme for SAGIN-UAV architectures.
• To mitigate performance degradation caused by the distinct characteristics of satellite and UAV networks.
• To optimize data transport in integrated space, air, and ground communication systems.

Main Methods:

• Developed an adaptive end-to-end congestion control scheme leveraging SAGIN characteristics.
• Optimized data injection during the slow-start phase for heterogeneous links.
• Implemented a high-precision loss differentiation mechanism to distinguish channel errors from congestion.

Main Results:

• Significantly reduced queuing delays at UAV nodes.
• Accelerated transmission efficiency across multi-hop UAV terminals.
• Enhanced data throughput in high-latency SAGIN-UAV environments.

Conclusions:

• The proposed adaptive scheme provides a resilient solution for SAGIN-enabled UAV networks.
• Optimized end-to-end transport control enhances overall network transmission capability.
• Effective management of diverse network conditions is crucial for integrated systems.