RRC success rate accessibility prediction on SAE/LTE network using Markov chain model

Abstract

Accessibility KPIs in SAE/LTE network are used to measure the success rate of users in accessing the network. The accessibility KPI is expressed in terms of probabilities that state how likely the user will be able to access the service for certain service times and conditions. Accessibility KPIs cover three areas to provide service ie. RRC success rate (RRC_SR), ERAB success rate and S1 setup success rate. In this study, future long-term performance of the RRC_SR, in term of KPI degradation will be predicted from existing historical data based on discrete time Markov Chain. Predicted KPI of RRC_SR in the long-run will be required in the failure management process for root cause analysis and to trigger preventive action. This is becoming increasingly important in line with the introduction of Self-Organizing Netwrok (SON) on SAE/LTE networks.