VoLTE Muting Probability Estimation and Prevention
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Solution Overview
Problem
VoLTE communication networks face frequent muting issues, which are typically addressed reactively after occurrence, impairing user experience and increasing inter-operator churn rates, necessitating proactive estimation and prevention of muting occurrences at various levels such as interfaces, nodes, or user equipment.
Innovation Solution
A system estimates muting probability using a muting probability estimation algorithm and determines corrective actions through a correlation algorithm to prevent muting occurrences by computing muting contribution per interface and implementing device-level delisting, parameter tuning, and software upgrades.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reactive resolution based on user complaints is used, then problem resolution is achieved, but user experience is highly impaired and churn rates increase
Solution Approach 1:
The system performs preliminary actions by proactively estimating muting probability for newly initiated calls using a muting probability estimation algorithm that computes muting contribution per interface. Corrective actions are determined before muting occurs through a correlation algorithm, preventing user experience impairment rather than reacting after complaints are received.
Solution Approach 2:
The system segments the muting problem analysis by computing muting contribution per interface (Uu, S1, S11, Rx) between calling and called UEs. This segmentation allows identification of specific interface-level causes and application of targeted corrective actions at the appropriate network layer.
2Reliability
If proactive estimation and prevention is implemented, then user experience is improved and churn rates are reduced, but system complexity increases
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring call state parameters (QCI, carrier, cell, MME, eNB, UE identifiers) and using a correlation algorithm to determine corrective actions based on estimated muting probability. The system applies corrective actions (parameter tuning, feature implementation, software upgrades) and can rollback if muting persists, creating a closed-loop feedback system that manages complexity through automated decision-making.
3Measurement precision
If interface-level muting contribution computation is performed, then precise muting estimation is achieved, but computational requirements increase
Solution Approach 1:
The system applies partial action by computing muting contribution per interface only for newly initiated calls rather than all calls. The correlation algorithm determines corrective actions based on the estimated muting probability, applying interventions only when and where needed, thus reducing overall computational energy requirements while maintaining precision for high-risk calls.
Data Source
AI summary
A system, method, and computer program product are provided for probabilistic estimation and prevention of muting occurrence in VoLTE. In operation, a system estimates a muting probability associated with a current state of a newly initiated call between calling user equipment (UE) and called UE by computing a muting contribution per interface between the calling UE and the called UE utilizing a muting probability estimation algorithm. Further, the system determines possible corrective actions to be performed specific to the current call state utilizing a correlation algorithm for prevention of muting occurrences.