Data collection concerning equipment operation in the network of a mobile operator

Abstract

Mobile data network operators face increasing operational complexity and rising maintenance costs as the number of equipment increases. As the number of base stations increases, so does the number of failures. Modern technological solutions based on neural network algorithms are able to predict in advance with a certain probability the occurrence of equipment failures. Data of operation and failures on the mobile network equipment is required to train a neural network model. The article considers the performed data collection on the 4G mobile operator network, features and limitations that may further affect the model training.