Finite-State Machine Root Cause Analysis for Call Failures
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Solution Overview
Problem
Existing solutions for determining the root cause of problematic calls in mobile communications systems, such as LTE and VoLTE networks, are inefficient, providing inaccurate diagnoses and requiring extensive manual analysis, which is time-consuming and costly, especially when dealing with large-scale networks.
Innovation Solution
A method involving the generation of an advanced signaling call flow that monitors finite states of calls and compares performance indicators to thresholds, using a Finite-State Machine (FSM) methodology to accurately determine the root cause of failures, reducing the need for manual analysis and costly probes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing manual analysis methods are used to determine root cause of call failures, then detailed diagnosis can be obtained, but the process is very time consuming and costly
Solution Approach 1:
The system performs self-diagnosis by automatically analyzing call failure data using the Finite-State Machine model. The network element itself generates the analysis results without requiring external manual intervention, thereby reducing both time and cost while maintaining diagnostic accuracy through automated root cause identification.
Solution Approach 2:
The patent replaces manual mechanical analysis processes with an automated computational system. The FSM-based automated analysis system substitutes human engineers' manual trace analysis with algorithmic processing, eliminating the time-consuming manual intervention while preserving diagnostic precision through systematic state transition analysis.
2Measurement precision
If existing manual analysis methods are used to determine root cause of call failures, then detailed diagnosis can be obtained, but extensive manual analysis is required which is costly
Solution Approach 1:
The patent segments the complex call failure analysis process into distinct finite states within the FSM model. Each state represents a specific phase of call processing, allowing the system to isolate and analyze specific failure points without requiring comprehensive manual examination of entire call traces, thereby reducing analytical complexity while maintaining precision.
Solution Approach 2:
The system changes the analysis parameters by transitioning from continuous manual trace review to discrete state transition monitoring. The FSM model converts complex call failure data into standardized state parameters that can be automatically compared and analyzed, reducing the complexity of manual analysis while preserving diagnostic accuracy through structured parameter evaluation.
3Loss of information
If existing solutions are used for root cause analysis, then some diagnosis information is provided, but the reasons indicated are very generic and may not provide enough information to make decisions
Solution Approach 1:
The patent applies partial action by focusing analysis only on the specific finite state where the failure occurred and its immediate transitions, rather than analyzing entire call traces. This targeted approach provides sufficient information for decision-making by concentrating on the critical failure point and its direct causes, eliminating unnecessary generic information while maintaining actionable insights.
Solution Approach 2:
The system performs preliminary action by pre-defining the Finite-State Machine model with all possible call processing states and transitions before analysis begins. This preliminary structuring enables the system to immediately identify and report specific failure states with actionable information, eliminating the need for generic diagnoses and providing decision-makers with precise, pre-processed failure information.
Data Source
AI summary
A method comprises generating an advanced signaling call flow and monitoring one or more finite states for one or more calls using the advanced signaling call flow. The method further comprises determining that there is a failure in one of the one or more monitored finite states for a particular call, and comparing one or more performance indicators to one or more respective thresholds, the one or more performance indicators associated with a cell in which the particular call took place and comprising information about the cell at the time of the failure. The method further comprises flagging one or more of the one or more performance indicators that do not satisfy their respective threshold, and determining a root cause of the failure based at least in part on one or more of the one or more flagged performance indicators and the advanced signaling call flow.