User Equipment Geolocation Using Static Moving Period Separation
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Solution Overview
Problem
Existing user equipment (UE) geolocation techniques in cellular communication systems face challenges in accurately estimating UE locations, especially for stationary UEs, due to high variability in network measurements, leading to errors and illogical route estimates, particularly with limited computational resources and significant noise in measurements.
Innovation Solution
The solution involves separating network measurement data into static and moving periods, applying specific processing techniques to each type to improve location accuracy, and merging the resulting information to enhance overall location estimation, using a combination of static and moving location processing to refine UE location data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If geotagging techniques estimate UE locations based on instantaneous network measurements or short history, then computational resources are conserved, but location estimation accuracy deteriorates
Solution Approach 1:
The patent segments the location estimation process into two distinct phases: a first location estimate derived from instantaneous measurements with limited computational resources, and a second location estimate derived from combining multiple historical measurements. This segmentation allows the system to conserve computational resources for real-time operations while improving accuracy through offline processing of historical data.
Solution Approach 2:
The patent performs preliminary action by pre-processing and storing historical network measurements before they are needed for location estimation. The network equipment maintains a database of historical measurements including cell IDs, timing advance values, and signal strength measurements, which can be quickly retrieved and combined with instantaneous measurements to generate improved location estimates without requiring heavy computational resources at the moment of estimation.
2Device complexity
If network measurements are collected over a very short time window, then computational complexity is reduced, but location estimation accuracy deteriorates due to high variability
Solution Approach 1:
The patent divides the measurement collection process into two segments: instantaneous measurements collected in real-time with low computational complexity, and historical measurements collected over extended periods and stored for later processing. This segmentation allows the system to maintain low computational complexity for real-time operations while accumulating sufficient data over time to improve location estimation accuracy through statistical processing of the combined measurement sets.
Solution Approach 2:
The patent introduces an intermediary component in the form of a database that stores historical network measurements. This intermediary acts as a buffer between the instantaneous measurement collection process and the location estimation process, allowing the system to maintain simple real-time operations while having access to a rich repository of historical data that can be processed to improve location accuracy without increasing real-time computational complexity.
3Adaptability or versatility
If location estimates are generated from varying measurements, then adaptability to different conditions is improved, but route estimate reliability deteriorates due to noise
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously compares instantaneous location estimates with historical location patterns and route information. The network equipment uses the stored historical measurements to provide feedback on expected location variations, allowing the system to distinguish between legitimate location changes due to UE movement and variations caused by measurement noise. This feedback loop improves route estimate reliability by filtering out inconsistent estimates while maintaining adaptability to genuine location changes.
Solution Approach 2:
The patent creates a composite location estimate by combining multiple measurement types and time periods. Instead of relying on a single measurement source, the system synthesizes location estimates from instantaneous measurements, historical measurements, route information, and pattern recognition results. This composite approach maintains adaptability to different measurement conditions while improving reliability through the diversification of data sources and the statistical processing that reduces the impact of noise from any single source.
Data Source
AI summary
The described technology is generally directed towards user equipment geolocation. Network measurement data associated with user equipment can be separated into static periods in which the user equipment was not moving, and moving periods in which the user equipment was moving. Static location processing can be applied to determine static locations from the static period network measurements, and moving location processing can be applied to determine moving locations from the moving period network measurements. Resulting static location information and moving location information can then be merged in order to improve the accuracy of both the static and the moving location information. The enhanced accuracy location information can be stored and used for any desired application.