Improving Cell Outage Management Through Data Analysis

Abstract

Self-Organizing Networks (SON) is an important feature for network management automation in the new generation of mobile communications. While SON have been considered as part of the recent 3rd Generation Partnership Project (3GPP) standards such as Long Term Evolution (LTE), it is expected that next 5th Generation (5G) mobile networks present new challenges for SON solutions. One of the most important use cases in Self-Healing is Cell Outage Compensation (COC). This paper proposes an important improvement of COC function based on analyzing large real data sets from live networks in order to adapt compensation to the real neighboring context. First, two methods (offline and online) to classify outages depending on the degraded metrics in neighboring cells are proposed and results for a set of cell outages occurred in a live LTE network are presented. Second, a method for estimating the lost traffic due to cell outages is proposed in order to quantify the load that cannot be intrinsically absorbed by neighboring cells. Finally, a novel COC methodology is proposed by taking into account the results obtained in the two previous studies.