IMPROVING CELL OUTAGE MANAGEMENT THROUGH DATA ANALYSIS

doi:10.1109/MWC.2017.1600076WC

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IMPROVING CELL OUTAGE MANAGEMENT THROUGH DATA ANALYSIS

2017-08-01

Isabel de-la-Bandera *

Pablo Muñoz

Inmaculada Serrano

Raquel Barco

DOI：10.1109/MWC.2017.1600076WC

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Abstract

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Self-organizing networks (SONs) are an important feature for network management automation in the new generation of mobile communications. While SONs have been considered to be part of the recent 3GPP standards such as LTE, it is expected that future 5G mobile networks will present new challenges for SON solutions. One of the most important use cases in self-healing is cell outage compensation (COC). This article proposes an important improvement in COC functionality based on analyzing large real data sets from live networks in order to adapt compensation to the real neighboring context. First, we propose two methods (offline and online) to classify outages depending on the degraded metrics in neighboring cells, and we present results for a set of cell outages occurring in a live LTE network. Second, we propose a method for estimating lost traffic due to cell outages 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.

Keywords:

FAULT-DETECTION

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