Wireless Link QoS Prediction with 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 actual and ideal time-frequency grids.
Innovation Solution
A method that determines the position and movement of a mobile transceiver to predict the received power and mismatch between the ideal and used time-frequency grids, considering factors like interference, noise, and resource availability to improve throughput prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional QoS prediction methods based on radio maps are used, then the prediction process is simple, but the accuracy of throughput prediction deteriorates due to not accounting for user mobility and time-frequency grid mismatch
Solution Approach 1:
The system performs preliminary determination of user position and movement information before throughput prediction. By obtaining position coordinates and movement characteristics (speed, direction) in advance, the system can predict future position and calculate time-frequency grid mismatch beforehand, improving prediction accuracy without adding complex real-time processing
Solution Approach 2:
The system dynamically adapts the prediction model by incorporating user movement information. Instead of using static radio map data alone, the method dynamically calculates time-frequency grid mismatch based on user velocity and direction, adjusting the prediction to match actual channel conditions for mobile users
2Measurement precision
If user mobility information is incorporated into QoS prediction, then the accuracy of throughput prediction improves, but the complexity of the prediction system increases due to additional measurements and calculations
Solution Approach 1:
The system utilizes self-service by leveraging existing network infrastructure components. The position information is obtained from existing location services, and movement information is derived from changes in position measurements that are already performed for other network functions, eliminating the need for separate dedicated measurement systems
Data Source
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AI summary
Embodiments relate to methods, computer programs and apparatuses for determining and using a predicted future quality of service of a wireless communication link between a transceiver, such as a base station or mobile transceiver, and a mobile transceiver. The method for predicting a future quality of service of a wireless communication link between a transceiver (100) and a mobile transceiver (200) comprises obtaining (110) information on a position and information on a movement of the mobile transceiver. The method comprises determining (120), based on the position of the mobile transceiver, a predicted received power of the wireless communication link at the mobile transceiver. The method comprises determining (130), based on the position and movement of the mobile transceiver, a predicted mismatch between an ideal time-frequency-grid configuration and a time-frequency-grid configuration used for the wireless communication link. The method comprises determining (160), 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, a predicted throughput of the wireless communication link. The method comprises determining (170), based on the predicted throughput of the wireless communication link, the predicted future quality of service of the wireless communication link.