Mobile Device Location Accuracy via Partial Ellipse Integral Model
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for determining the location of a mobile device based on Call Data Records (CDRs) suffer from low accuracy due to large cell coverage and uncertain wireless signal strength, especially when the device is at the edge of a cell and undergoes frequent handovers.
Innovation Solution
A method and apparatus that analyze CDRs to determine the first cell and time spent moving to a second cell, using probability densities based on the mobile device's moving speed to pinpoint possible locations within the first cell, employing a partial ellipse integral model to establish error ellipses and integrate probability densities for accurate location determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If location is determined based on CDR alone using cell ID, then the method is simple, but the location accuracy is low due to large cell coverage
Solution Approach 1:
The patent transforms the location determination from discrete cell ID to continuous probability density distribution by introducing movement speed and time parameters, achieving higher precision while maintaining computational feasibility
Solution Approach 2:
The patent adds temporal and velocity dimensions to the traditional spatial cell-based location model, creating a four-dimensional probability density function that significantly improves location precision
2Measurement precision
If cell coverage is reduced to improve location precision, then location accuracy improves, but the device complexity increases due to multiple cells and handovers
Solution Approach 1:
The patent creates a universal probability density calculation model that works across different cell sizes and handover scenarios, handling both large-cell and small-cell environments with the same mathematical framework
Solution Approach 2:
The patent introduces dynamic elements (movement speed, time duration) to the static cell-based model, allowing the system to adapt to varying mobility patterns and handover frequencies without increasing structural complexity
3Measurement precision
If probability density calculation is performed for all locations, then location precision improves, but the calculation complexity increases
Solution Approach 1:
The patent reduces calculation complexity by changing the integration parameters from spatial coordinates to movement-based parameters (speed, time, direction), enabling efficient probability density calculation without exhaustive spatial sampling
Data Source
AI summary
A method and an apparatus for determining a location of a mobile device. The location of a mobile device is determined accurately according to information which includes call data records of the mobile device. By employing a partial ellipse integral model, two physical world factors are taken into consideration in reducing the location uncertainty in call data records. The factors include: spatiotemporal constraints of the device's movement in the physical world and the telecommunication cell area's geometry information, which increase the accuracy of determining the location of a mobile device.