Dynamic Tag Control for Event-Based Position Clustering
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Solution Overview
Problem
Current positioning methods in cellular communications networks are not responsive to events such as poor radio quality or emergency positioning requests, and are geographically static, unable to handle quickly moving or varying regions.
Innovation Solution
A method and arrangement for dynamic event-based clustering of high-precision position measurements, where events are detected, tagged with specific information, and used to obtain local clusters of measurements, allowing for responsive and adaptive positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cell identity positioning method is used, then response time is very low and implementation is straightforward, but positioning accuracy is limited by cell size
Solution Approach 1:
The patent segments the cell coverage area into multiple clusters based on high-precision reference measurements. Instead of treating the entire cell as one uniform area, it divides it into smaller clusters with distinct positioning characteristics, thereby improving accuracy without requiring a complete overhaul of the cell identity method.
Solution Approach 2:
The patent performs preliminary clustering of high-precision reference measurements during idle periods or in advance of actual positioning events. This pre-computation allows the system to quickly retrieve pre-defined clusters during emergency positioning, maintaining low response time while improving accuracy.
2Adaptability or versatility
If geographically static positioning regions are used, then system implementation is simple, but the system cannot handle quickly moving or varying regions
Solution Approach 1:
The patent introduces dynamic tag control that allows clusters to be associated with moving objects or events. Tags can be updated in real-time to reflect changing positions, enabling the system to track moving clusters while maintaining the underlying static infrastructure.
Solution Approach 2:
The system uses feedback from detected events (such as emergency calls or radio quality changes) to dynamically update cluster associations. When an event is detected, the system retrieves or creates appropriate clusters based on current conditions, allowing adaptive response to changing situations.
3Measurement precision
If comprehensive high-precision positioning is continuously performed, then positioning accuracy is maximized, but system resource consumption increases
Solution Approach 1:
Instead of continuous positioning, the system performs high-precision measurements periodically or only when triggered by specific events. Reference measurements are collected at intervals or upon event detection, reducing overall resource consumption while maintaining accuracy when needed.
Solution Approach 2:
The system changes measurement parameters dynamically - using low-accuracy cell identity positioning during normal operation and switching to high-precision A-GPS or other accurate methods only when events are detected or during emergency situations, optimizing the balance between accuracy and resource usage.
Data Source
AI summary
In a method for clustering position determination for providing position determination assisting data in a cellular communications network, detecting S1 an event, such as the occurrence of an emergency call or sudden drop in radio quality, providing a tag S2 for the detected event comprising event specific information. Subsequently, providing S3 high precision position measurements the said tagged detected event, and repeating S4 said detecting and providing steps a plurality of times. Finally, obtaining local clusters S5 of high-precision position measurements based on the event specific tag.