Vehicle QoS Mapping for Multi-RAT Radio Link Prediction

The patent introduces a prediction entity that acts as an intermediary between multiple RATs and the application. This entity generates predictive QoS information by processing measurements from different RATs (LTE-V, 5G-V2X, DSRC) and provides unified predictions to applications, thereby simplifying the coordination complexity while maintaining improved communication performance through multi-RAT utilization

The prediction entity is designed to handle multiple RATs simultaneously with a single unified interface to applications. It can process measurements from LTE-V, 5G-V2X, and DSRC channels through a common prediction mechanism, making the system multi-functional without requiring separate prediction systems for each RAT, thus reducing overall device complexity

The patent combines multiple measurement factors (mobile transceiver density, distance between transceivers, antenna characteristics, and RAT availability) into a unified QoS prediction framework. By merging these diverse measurements through a single prediction entity that uses statistical models or machine learning, the system achieves high prediction accuracy without requiring separate complex processing systems for each factor

The prediction entity transforms multiple physical parameters (density, distance, antenna properties) and RAT availability indicators into a unified predictive QoS metric. This parameter transformation approach allows accurate QoS prediction while simplifying the processing effort by converting diverse measurements into a standardized prediction output through statistical or machine learning models