Geolocation Calibration Engine for Wireless Network Accuracy
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Solution Overview
Problem
Current geolocation technologies in wireless networks face challenges in achieving high accuracy, particularly due to limitations in drive testing costs and the need for improved position information for various location-based applications, where existing methods like triangulation and GPS may not provide sufficient precision.
Innovation Solution
A self-calibrating geolocation analytic system that combines measurement data from wireless networks with external geo-location data sources, such as GPS and Minimizing Drive Test (MDT) data, to estimate and correct errors, thereby enhancing location accuracy through a predictor database and calibration engine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If drive testing is performed to improve geolocation accuracy, then measurement precision is improved, but cost increases and productivity decreases
Solution Approach 1:
The system performs automatic self-calibration by utilizing existing network signaling data and external geolocation sources. The calibration engine automatically processes measurement data from multiple sources, compares it with external references, and adjusts geolocation parameters without requiring manual drive testing, thereby achieving continuous self-improvement of accuracy
Solution Approach 2:
The calibration engine serves multiple functions simultaneously: it processes triangulation data, GPS data, MDT data, and other geolocation measurements from various sources using a unified algorithmic framework. This multi-functional approach eliminates the need for separate calibration procedures for different data types
2Measurement precision
If external reliable geolocation sources are used to improve accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The calibration engine acts as an intermediary that receives and harmonizes data from multiple external geolocation sources (GPS, MDT, triangulation systems). It processes these diverse inputs through unified algorithms and produces standardized calibration outputs, thereby managing complexity through a central coordinating component
Solution Approach 2:
The system merges multiple geolocation data sources and calibration methods into a unified processing framework. By combining triangulation data, GPS references, and MDT measurements through integrated algorithms, the system achieves improved accuracy without requiring separate complex systems for each data type
Data Source
AI summary
A method for calibrating geolocation analytic system in a wireless network includes receiving a first data set including measurement data associated with a mobile device connected to the wireless network from a first data source. A second data set comprising external geo-location data associated with the mobile device is received from a second data source. The first data set is compared to the second data set to estimate geo-location of the mobile device and to identify one or more errors using calibration function. The identified one or more errors are corrected based on the comparison.