## 6 Conclusions  
The present work has presented the primary information sources and key approaches for monitoring in current cellular network OAM, while identifying their shortcomings. As a means to solve them, vUE probes have been demonstrated to be a very relevant tool. From this, an integrated framework for its application has been designed, establishing its capabilities to support advanced monitoring and management tasks. The different parts that would be necessary for integration with the network management system have been described, along with the mechanisms for their operation and implementation. Then, a summary of all the efforts made so far to be able to integrate the data obtained from the user in the automatic network management for various purposes has been presented in addition to the works that propose the virtualization of probes in any of its conceptions. A real-world implementation of this framework has demonstrated the capabilities of the proposed approach for advanced QoE analysis and the identification of the relations between the large number of parameters involved in the service provision, and provided novel insights on how crowd-events can affect the network performance. In this sense, it has been studied how the occurrence of an event, by its nature, produces a pattern of degradation in specific time periods. It has also been shown how the correlations of the radio parameters with the performance indicators or KQI can vary depending on the configuration or strategy of the operator for users in the same relative positions. Thus, the benefits of using vUE have been synthesized by taking advantage of the technological momentum of the co-evolution of virtualization and open radio platform technologies, together with the rapid development of new user applications. The identified open research areas and challenges pave the way for further research and developments in the field to guide future tools for advanced cellular network management. As future work, a more extensive study of the measurement campaign, including analysis of variance (ANOVA) and the inclusion of the MAC and RRC network layers, would complete the analysis provided here. Conceptualization, E.B. and S.F. ; methodology, E.B. ; software, E.B. ; investigation, E.B. ; resources, H.L., M.X, R.B. and O.A. ; writing--original draft preparation, E.B. and S.F. ; writing--review, editing, E.B., S.F., R.B., M.X. and O.A. ; supervision, O.A. and R.B. ; project administration, O.A., H.L., R.B. and S.F. ; funding acquisition, R.B. and O.A. All authors have read and agreed to the published version of the manuscript. This research has been carried out within the framework of Horizon 2020 projects MONROE--Measuring Mobile Broadband Networks in Europe (H2020-ICT-11-2014, grant number 644399). This work has been partially funded by Junta de Andalucia and ERDF in the framework of the projects IDADE-5G (UMA18-FEDERJA-201, \"Programa Operativo FEDER Andalucia 2014-2020\"), PENTA (P18-FR-4647, \"Proyectos de investigacion en colaboracion con el tejido productivo\") and 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\"). It has been also performed in the framework of the Horizon 2020 project LOCUS (ICT-871249) receiving funds from the European Union. Not applicable. The authors declare no competing interests. The following abbreviations are used in this manuscript: