Resilience analysis and quantification method for 5G-Radio Access Networks

A 5G Radio Access Network (5G-RAN) can be disturbed or shutdown due to a variety of failures, in spite of advanced optimization techniques and self-healing methods. Recently, operators started to take an interest in improving the resilience of communication networks with adaptive compensation techniques to mitigate outage-induced performance degradation. However, for the sake of effective and efficient resilience management, it is vital to be able to measure current and prospective resiliency levels of a given 5G-RAN using relevant and explicit metrics. Thus, the characterisation of resilience goes over a thorough analysis of 5G-RAN performance indicators followed by a rigorous quantification of current and future levels of resilience. In this work, we perform an analysis and a quantification of 5G-RAN resilience using a coverage indicator. It is known as a main performance indicator for network planners and operators, coverage is a necessary prerequisite to ensure a certain level of Quality of Service. For that, we model the network coverage using Continuous Time Markov Chains (CTMCs) where coverage status is characterized with multiple states defined with Reference Signal Received Power (RSRP) signal. The proposed Markov model is analytically studied allowing to perform quantitative analysis, predict coverage outage and provide resilience quantification. Using our model, we conduct numerical analysis of several usage scenarios and propose a resilience framework to show the usability of our proposed approach.