Wireless Link QoS Prediction Using Mobility-Aware Grid Mismatch
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Solution Overview
Problem
Existing methods for predicting the quality of service (QoS) of wireless communication links do not adequately account for the mobility of users, leading to inaccuracies in throughput prediction due to mismatches between the time-frequency-grid used and the ideal grid adapted to the movement of mobile transceivers.
Innovation Solution
A method that determines the position and movement of mobile transceivers to predict the received power and mismatch between the ideal and used time-frequency-grids, considering factors like delay-Doppler spread, interference, and receiver noise power to enhance throughput prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing QoS prediction methods are used, then the prediction process is simple, but the accuracy of throughput prediction deteriorates due to not accounting for user mobility and grid mismatches
Solution Approach 1:
The system performs preliminary determination of mobile transceiver position and movement information before QoS prediction. By obtaining position data and movement characteristics in advance, the system can calculate the ideal time-frequency grid configuration beforehand, enabling more accurate throughput prediction that accounts for mobility-induced grid mismatches.
Solution Approach 2:
The patent introduces an intermediary calculation step that determines the mismatch between the ideal time-frequency grid (adapted to mobile transceiver movement) and the actually used grid. This intermediary metric serves as a bridge between mobility parameters and throughput prediction, enabling accurate QoS estimation without requiring complete redesign of the prediction framework.
2Measurement precision
If the ideal time-frequency-grid adapted to mobile transceiver movement is used, then the throughput prediction accuracy improves, but the complexity of determining the grid configuration increases
Solution Approach 1:
The system determines the ideal time-frequency grid configuration locally adapted to each mobile transceiver's specific movement characteristics. By calculating grid parameters based on individual user position and movement information, the system achieves accurate local optimization without requiring complex global grid management, thus improving prediction accuracy while controlling complexity.
3Measurement precision
If position and movement information of mobile transceivers is obtained, then the QoS prediction accuracy for fast-moving transceivers improves, but the amount of information processing increases
Solution Approach 1:
The system extracts only the essential position and movement information needed for QoS prediction, rather than processing complete trajectory data or all possible mobile transceiver parameters. By selecting and processing only the critical mobility parameters that directly affect time-frequency grid mismatch, the system achieves improved prediction accuracy while minimizing information processing volume.
Data Source
AI summary
Methods, computer programs, and apparatuses for determining and using a predicted future quality of service of a wireless communication link between a transceiver and a mobile transceiver. The method includes obtaining information on a position and a movement of the mobile transceiver, determining a predicted received power of the wireless communication link at the mobile transceiver based on the mobile transceiver position, determining a predicted mismatch between an ideal time-frequency-grid configuration and a time-frequency-grid configuration used for the wireless communication link based on the position and movement of the mobile transceiver, determining a predicted throughput of the wireless communication link based on the predicted received power and based on the predicted mismatch between the ideal time-frequency-grid configuration and the time-frequency-grid configuration used for the wireless communication link, and determining the predicted future quality of service of the wireless communication link based on the predicted throughput of the wireless communication link.