# Location-Awareness for Failure Management in Cellular Networks: An Integrated Approach
## 5 Conclusions & Outlook  
The present work has proposed a complete framework, denominated as CAFAIM, for the generation and cost-efficient application of location to support cellular failure management. This is achieved by the generation of indicators combining both cellular and localization information based on the automatic definition of different areas of interest and the calculation of their associated statistics. The resulting contextualized indicators are then processed through feature engineering techniques to improve the performance of posterior inference mechanisms for cellular network management.  
The resulting framework is, in this way, expected to provide support to inference mechanisms making use of the generated indicators. The capabilities of this approach have been evaluated in an highly-dynamic indoor ultra-dense network and with the objective of supporting the classification of different key network failures. Here, the performance of a set of multi-class classifiers has been assessed while considering classical approaches in comparison to the full implementation of the proposed approach via the application of the generated contextualized indicators and different feature-engineering techniques.  
Hence, the proposed use of the automatically generated metrics (combining positioning and network data) as their posterior FE processing has demonstrated the capabilities of the approach in improving the accuracy of network failure classification under variable user densities concentrations, and cell locations. This is achieved across the different tested classifiers, while also providing reduced computational costs.  
Figure 8: Execution times of the classifiers for the different combinations of classic and contextualized indicators.  
Future work will study the application of the presented approach with additional context variables, and based on the definition of additional approaches for the generation o indicators and the classification process. Moreover, while the focus of the developed framework has been in its use to indoor ultra-dense networks, its performance in such highly dynamic scenario opens the way for future studies on its applicability to other environments that are characterized by a high mobility, especially those related with vehicles and outdoor areas.  
Conceptualization, S.F., C.B.; methodology, S.F., C.B.; software, S.F., C.B., J.V.; validation, S.F., M.Z.A., C.B.; formal analysis, S.F., C.B.; investigation, S.F., C.B., E.B.; resources, R.B., M.Z.A.; writing--original draft preparation, S.F., C.B., J.V.; writing--review, editing, S.F., R.B., C.B., E.B.; supervision, R.B., S.F.; project administration, M.Z.A., S.F., R.B.; funding acquisition, R.B., S.F., M.Z.A. All authors have read and agreed to the published version of the manuscript.  
This work has been partially supported by Business Finland (grant no.1916/31/2017). It has been also performed in the framework of the Horizon 2020 project LOCUS (ICT-871249) receiving funds from the European Union. This work has been also partially funded by Junta de Andalucia and ERDF in the framework of the projects IDADE-5G (UMA18-FEDERJA-201, \"Program Operativo FEDER Andalucia 2014-2020\"), PENTA (\"Proyecto de Excelencia PENTA, P18-FR-4647\"P18-FR-4647\", \"Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades\") and SMART (\"Sistema de Monitorizacion y analisis Automatico de Redes de Telecomunicacion (SMART)\", \"Incentivos a los agentes publicos del Sistema Andaluz del Conocimiento, para la realizacion de proyectos de I+D+i, en el ambito del Plan Andaluz de Investigacion, Desarrollo e Innovacion PAIDI 2020\").  
Not applicable.  
The authors declare no conflict of interest.