UE Positioning via Virtual Reference Sources and Kalman Filtering
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Solution Overview
Problem
Current wireless communication networks face challenges in accurately determining user equipment (UE) positioning, particularly in scenarios with limited reference nodes or poor geometric dilution of precision (GDOP), leading to reduced location accuracy and reliability.
Innovation Solution
The implementation of enhanced positioning algorithms that utilize additional telemetry parameters, such as signal location parameters from multiple channel components, including line-of-sight and non-line-of-sight signals, combined with recursive filtration techniques like Kalman filtration, and the concept of virtual reference sources to improve location accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional positioning methods using reference nodes are used, then positioning can be performed, but positioning accuracy deteriorates in scenarios with limited reference nodes or poor geometric dilution of precision
Solution Approach 1:
The patent introduces virtual reference sources as intermediary elements that do not physically exist in the network but are mathematically constructed based on measurements from real reference nodes. These virtual sources act as mediators to improve positioning accuracy by providing additional geometric diversity and reducing GDOP, especially in scenarios with limited reference nodes. The virtual reference sources are generated by processing multipath channel measurements and telemetry parameters to create fictitious signal sources that enhance the positioning geometry.
Solution Approach 2:
The patent transforms the positioning approach by changing from using only direct line-of-sight measurements to utilizing multipath channel measurements including non-line-of-sight signals. By processing these additional parameter types (telemetry parameters, signal location parameters from multiple channel components) through recursive filtration techniques like Kalman filtration, the system converts harmful multipath effects into useful positioning information, thereby improving accuracy in challenging environments.
2Measurement precision
If additional telemetry parameters and multipath measurements are utilized, then positioning accuracy improves, but computational complexity increases
Solution Approach 1:
The patent applies recursive filtration techniques such as Kalman filtration to pre-process telemetry parameters and multipath measurements before they are used for positioning calculations. This preliminary action filters out noise and redundant information, organizing the complex data into refined estimates that can be more efficiently processed in subsequent positioning steps, thereby reducing the overall computational burden despite handling additional parameters.
Solution Approach 2:
The patent creates virtual reference sources that are mathematical copies or representations of the positioning problem, constructed from measurements of real reference nodes. Instead of directly processing complex multipath measurements from multiple real nodes, the system creates simplified virtual representations that capture the essential geometric relationships, making the positioning calculations more tractable while maintaining accuracy.
Data Source
AI summary
Methods, systems, and storage media are described for the measurement and reporting of user equipment (UE) positioning in cellular networks. Other embodiments may be described and/or claimed.