A cross-layer scheduling optimization method for a vehicle-mounted starlink protocol stack and a related device
By constructing a cross-layer information fusion mechanism and reinforcement learning algorithm in the vehicle-mounted StarSignal protocol stack, a cross-layer collaborative scheduling strategy is generated, which solves the shortcomings of the vehicle-mounted StarSignal protocol stack in cross-layer collaboration, quality of service assurance and dynamic adaptability, and improves resource utilization and communication stability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-04-28
- Publication Date
- 2026-07-17
AI Technical Summary
The existing vehicle-mounted StarFlash protocol stack has shortcomings in cross-layer collaboration, quality of service assurance, and dynamic adaptability, resulting in low resource utilization, difficulty in meeting differentiated business needs, and poor communication stability in complex vehicle environments.
By constructing a cross-layer information fusion mechanism, establishing an end-to-end service quality requirement database, and using reinforcement learning algorithms to generate cross-layer collaborative scheduling strategies, deep collaboration between the physical layer, MAC layer, and network layer is achieved, and dynamic scheduling optimization is performed in conjunction with standardized cross-layer interfaces.
It significantly improved resource utilization and transmission efficiency, ensured the service quality of differentiated services, and enhanced the stability and scenario adaptability of the communication system.
Smart Images
Figure CN122420871A_ABST