Geolocation Data Prioritization for Wireless Fault Detection
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Solution Overview
Problem
Existing wireless communication systems face challenges in efficiently locating faults due to the vast volume of data generated, leading to delayed fault detection and diagnosis, as conventional methods either store all data, rely on sampling, or conduct time-consuming drive tests, which are inadequate for real-time analysis and precise geolocation.
Innovation Solution
A geolocation data prioritization system that processes all call session data from multiple sectors in real-time, creating a high-priority data stream to provide immediate geolocation data, allowing for near real-time fault detection and reducing the need for extensive data storage and operator intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all call session data is stored for fault analysis, then complete fault information is available, but storage capacity and access time become insufficient
Solution Approach 1:
The system extracts only the most relevant call session data elements needed for fault detection and geolocation, separating critical information from the complete data set. This allows storing essential fault analysis information without requiring storage of all raw call data, resolving the contradiction between information completeness and storage volume.
Solution Approach 2:
The call session data is segmented into different priority levels and categories. High-priority data elements essential for fault detection are extracted and stored separately, while less critical data can be discarded or stored in lower-priority storage. This segmentation enables complete fault information to be available without storing the entire data set.
2Loss of information
If conventional data storage methods are used, then all call data is preserved, but fault detection time increases to hours or days
Solution Approach 1:
The system performs preliminary processing and prioritization of call session data as it is generated, identifying and flagging potentially fault-related data elements in real-time. This preliminary action ensures that when a fault occurs, the relevant information is already prepared and readily accessible, eliminating the need to search through stored data later and reducing fault detection time.
Solution Approach 2:
The system continuously monitors call session data and provides feedback about network conditions and potential faults in real-time. This ongoing feedback mechanism allows immediate detection and response to faults without waiting for batch processing or manual analysis, significantly reducing fault detection time while preserving necessary data.
3Measurement precision
If data is processed in batch after monitoring period, then comprehensive analysis is possible, but results are available more than a day after fault reporting
Solution Approach 1:
The system processes call session data continuously in real-time rather than in batch operations. Data prioritization and fault detection algorithms operate continuously on incoming data streams, ensuring that fault analysis is performed immediately as data becomes available. This continuous processing maintains comprehensive analysis capability while eliminating the delays inherent in batch processing approaches.
4Quantity of substance
If probes are installed for limited time periods, then data collection is manageable, but faults may only be detected if they re-occur during monitoring
Solution Approach 1:
The system automatically identifies and prioritizes fault-related data elements without requiring manual probe installation or configuration. The automated data prioritization continuously monitors all call session data, ensuring that faults are detected regardless of when they occur. This self-service approach eliminates the need for time-limited manual monitoring while maintaining manageable data collection volumes through automated filtering.
Data Source
AI summary
Communication session data from a mobile radio communications network (100) is processed to extract substantially all communication session data relating to calls in at least two sectors of the network. This processing occurs as the communication session data becomes available, thereby providing a stream of communication session data (210). From the stream of communication session data (210), a high priority data stream (220) is created. The high priority data steam (220) comprises a minority of the communication session data for each call in the at least two sectors of the network (100). Geolocation data (230) is produced for each call. An immediately accessible copy of both the high priority data stream (220) and the geolocation data (230) is provided, for each call.