Network Quality Monitoring via Usage Message Callback Analysis
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Solution Overview
Problem
Current methods for determining mobile telephony network quality are inadequate as they often miss user-experienced issues, are expensive, and provide incomplete or non-representative data, failing to offer a comprehensive view of network performance without modifying the network or adding sensors.
Innovation Solution
A method and system that utilize existing network equipment to acquire and analyze Usage Messages (UMs) to calculate indicators of transmission quality, including callback rates, without adding sensors, by filtering and characterizing UMs based on date, caller, and call type, and using algorithms to determine quality and trigger interventions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors and testers are installed to monitor network quality, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The network elements themselves (MSCs, BTSs) generate and provide the usage message data needed for quality assessment. The existing network infrastructure serves its own monitoring needs by producing usage records that can be analyzed to determine quality indicators, eliminating the need for separate monitoring sensors and testers
Solution Approach 2:
The usage messages originally designed for billing and accounting purposes are repurposed to serve dual functions: traditional network operations and quality of service monitoring. This multi-functionality allows the same data infrastructure to support both commercial and quality assessment needs without additional dedicated monitoring systems
2Device complexity
If technical indicators are used to monitor network status, then device complexity is reduced, but measurement precision deteriorates as user-experienced issues are missed
Solution Approach 1:
The system establishes feedback loops by continuously collecting usage messages and analyzing callback patterns to detect quality deterioration. The callback rate serves as a feedback indicator that reflects actual user experience, allowing the system to identify and respond to quality issues that traditional technical indicators would miss
Solution Approach 2:
The usage messages act as an intermediary carrier that bridges the gap between simple technical monitoring and accurate quality assessment. By analyzing the content and patterns of these messages (particularly callback behaviors), the system translates raw network data into meaningful quality indicators that reflect user experience without requiring complex direct measurement apparatus
3Measurement precision
If manual analysis of usage messages is performed, then measurement precision is improved, but productivity deteriorates
Solution Approach 1:
The patent replaces manual mechanical analysis of usage messages with automated electronic processing systems. Computers and software algorithms automatically collect, filter, group, and analyze usage message data to calculate quality indicators, eliminating the need for manual review while maintaining or improving both precision and processing speed
Solution Approach 2:
The system performs preliminary automated filtering and grouping of usage messages by relevant criteria (time periods, network elements, user groups) before detailed quality analysis. This preliminary organization of data prepares the information for efficient processing and enables rapid generation of quality indicators without manual intervention
Data Source
AI summary
A method for determining deteriorations in the quality of a mobile or fixed telephony network on a day D (or at any other frequency, for example hour or minute) by implementing one or more items of special equipment in the network, wherein the method implements at least one measurement means and at least one calculation means, characterised in that the method including at least: a stage for selecting (S1) the Usage Messages (MU) (1) corresponding to each call of the day D (2a) or at any other frequency (for example hour or minute); a stage for characterising (S2) groups of UMs corresponding to the callbacks from among the UMs of the calls selected (4); a stage for filtering (S3a) the UMs in order to separate the UMs called “incoming—outgoing” (5), the UMs called “return incoming” (6) and the UMs called “return outgoing” (7); a stage for calculating at least one indicator (S7) by grouping the UMs (15) as a function of several common data fields; a stage for calculating the callback rates for an indicator; a stage for intervening to restore or improve the quality of the calls in the section of the network defined by at least one field code common to several UMs.