Data intelligence in fault detection in a wireless communication network

An apparatus comprising:

• a non-transitory storage medium;
• and
• instructions stored in the non-transitory storage medium, the instructions being executable by the apparatus to:
• gather performance measurement data related to point-to-point performance measurements of a wireless communication network;
• determine correlations among at least some of the performance measurements;
• based at least in part on the correlations, analyze a first portion of the performance measurement data;
• based at least in part on the analyzing, create a prediction model for predicting causes of faults within the wireless communication network;
• obtain root cause fix history data related to past faults within the wireless communication network;
• based at least in part on the root cause fix history data, verify the prediction model with a second portion of the performance measurement data;
• and
• apply the prediction model to future faults within the wireless communication network to predict potential causes of the future faults.

A wireless communication network comprising:

• one or more processors;
• a non-transitory storage medium;
• and
• instructions stored in the non-transitory storage medium, the instructions being executable by the one or more processors to:
• gather performance measurement data related to point-to-point performance measurements of the wireless communication network;
• determine correlations among at least some of the performance measurements;
• based at least in part on the correlations, analyze a first portion of the performance measurement data;
• based at least in part on the analyzing, create a prediction model for predicting causes of faults within the wireless communication network;
• obtain root cause fix history data related to past faults within the wireless communication network;
• based at least in part on the root cause fix history data, verify the prediction model with a second portion of the performance measurement data;
• and
• apply the prediction model to future faults within the wireless communication network to predict potential causes of the future faults.