METHODS AND SYSTEMS FOR EVALUATING VOICE OVER WI-FI (VoWiFi) CALL QUALITY

A device comprising:

• a communication interface;
• a memory, wherein the memory stores instructions;
• and
• a processor, wherein the processor executes the instructions to:
• receive a plurality of training data points, wherein each data point in the plurality of training data points includes a voice call quality value and values for a plurality key performance indicators (KPIs) related to voice over wi-fi voice call quality;
• determine, for each KPI of the plurality of KPIs and using the plurality of training data points, a correlation between the KPI and the voice call quality value;
• select a subset of the plurality of KPIs based on the correlation;
• perform a plurality of discrete regression analyses based on the subsets of the plurality of KPIs and the voice call quality values to generate a plurality of regression results;
• determine an accuracy for each of the plurality of regression results;
• assign weights to each of the plurality of regression results based on the determined accuracies;
• combine the plurality of regression results using the assigned weights to generate a final combined estimated VoWiFi voice call quality algorithm that accurately predicts the voice call quality value based on values for the selected subset of the plurality of KPIs;
• receive, via the communication interface, a new subset of the plurality of KPIs;
• and
• determine the estimated voice over Wi-Fi (VoWiFi) voice call quality value based on the combined estimated VoWiFi voice call quality algorithm and the new subset of the plurality of KPIs.

A non-transitory, computer-readable storage medium storing instructions executable by a processor of a computational device, which when executed cause the computational device to:

• receive a plurality of training data points, wherein each data point in the plurality of training data points includes a voice call quality value and values for a plurality key performance indicators (KPIs) related to voice over wi-fi voice call quality;
• determine, for each KPI of the plurality of KPIs and using the plurality of training data points, a correlation between the KPI and the voice call quality value;
• select a subset of the plurality of KPIs based on the correlation;
• perform a plurality of discrete regression analyses based on the subsets of the plurality of KPIs and the voice call quality values to generate a plurality of regression results;
• determine an accuracy for each of the plurality of regression results;
• assign weights to each of the plurality of regression results based on the determined accuracies;
• combine the plurality of discrete regression results using the assigned weights to generate a final combined estimated voice over Wi-Fi (VoWiFi) voice call quality algorithm that accurately predicts the voice call quality value based on values for the selected subset of the plurality of KPIs;
• receive a new subset of the plurality of KPIs;
• and
• determine the estimated VoWiFi voice call quality value based on the combined estimated VoWiFi voice call quality algorithm and the new subset of the plurality of KPIs.