Network Error Detection via Spatio-Temporal Signal Analysis
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Solution Overview
Problem
Existing communication network technologies face challenges in reliably identifying sources of performance degradation in mobile devices, particularly due to complex terrain, radio-frequency interference, and unpredictable noise sources, which are difficult to diagnose using signal strength measurements alone.
Innovation Solution
A method and system that collect signal quality data from clients with fixed external antennas over extended periods, comparing new data with previous data to identify anomalies, and determine the source of errors based on time and position, using statistical analysis and pattern recognition to isolate issues such as malfunctioning base stations or radio-frequency interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If signal strength measurement is used for error detection, then the measurement process is simple, but the ability to identify hardware problems and complex noise sources is insufficient
Solution Approach 1:
The patent segments the error detection process into multiple independent measurement dimensions: signal strength, signal quality, time stamps, and geographic positions. By dividing the measurement into these separate components and analyzing their relationships, the system achieves both operational simplicity and high identification accuracy for hardware problems and noise sources.
2Measurement precision
If complex analysis methods are used to identify noise sources, then the identification accuracy improves, but the system complexity increases
Solution Approach 1:
The patent introduces geographic position and time as intermediary parameters that mediate between the raw signal measurements and the final noise source identification. These intermediaries provide a spatial-temporal framework that simplifies the analysis of complex noise patterns without requiring sophisticated signal processing algorithms.
3Ease of operation
If information is collected via the hardware itself, then the collection process is straightforward, but the ability to reliably identify hardware problems is compromised
Solution Approach 1:
The patent inverts the traditional approach by using the client device to collect not only signal data but also its own geographic position and time information. This inverted perspective allows the system to observe hardware performance from the user's viewpoint, enabling reliable identification of hardware problems through pattern recognition in the collected data without complicating the collection process.
4Loss of time
If measurements are taken over short periods, then the data collection time is reduced, but the ability to detect inconsistent noise sources is limited
Solution Approach 1:
The patent transitions from time-only analysis to spatio-temporal analysis by incorporating geographic position as an additional dimension. This allows the system to detect inconsistent noise sources by identifying patterns that repeat at specific locations regardless of when they occur, effectively extending the detection capability without requiring prolonged measurement periods.
Data Source
AI summary
A method for identifying a source of error in a communication network including at least one client configured to be connected to a base station is disclosed. The at least one client is arranged on a vehicle repetitively moving in a predetermined area. The method includes the steps of: collecting signal quality data from the at least one client for an extended time period when moving in the area, the signal quality data including a plurality of data entries; determining a position in the area at which each of the data entries was collected and a time at which each of the data entries was collected; identifying an anomaly in the signal quality data, by comparing newly collected signal quality data with previously collected data. A source of error may be determined from the time and position when the signal quality data having an anomaly was collected.