Failure management insights in 5G using ns-3 network simulator

Failure management has been one of the most researched fields in cellular networks paradigm. Networks operators has experienced many problems on their deployments with each of the past generations. 5G networks aim high to encompass a wide variety of services, which means a large amount of resources on network management and failure resolution. The objective of the present work is to use the previous generation as base and provide, together with the updates on 3GPP specification, insights about what would be the problems that networks will handle. For this, they were identified and categorized some of these failures at the same time their effect on system performance was evaluated.This work was supported by the European Union’s Horizon 2020 research and innovation program under Grant no. 871249, project LOCUS. This work has been also funded by: Junta de Andalucía and ERDF: projects IDADE-5G (UMA18-FEDERJA-201) and OptiRAN5G (UMA18-FEDERJA-174), and postdoctoral grant (Ref., DOC 01154, “selección de personal investigador doctor convocado mediante Resolución de 21 de mayo de 2020”, PAIDI 2020); University of Malaga, through the I Plan Propio de Investigación, Transferencia y Divulgación Científica de la Universidad de Málaga. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

UE side Application Layer metrics For QoE-based Network Management.

Cellular networks are being improved by the automation of management tasks in order to optimize the performance while improving the efficiency. This is based on the vast amount of data which is available from the network side. Nonetheless, the network side perspective is limited and the focus is being redirected to the user side. Here, Drive Tests are in charge of collecting useful information, but at high costs. Thus, the present work presents a key source of information regarding network management: user side application layer metrics. In this regard, this work exploits this user side data by using different techniques to estimate the users’ quality of experience with the aim of network management.This work was supported by the project MUSE (Massive User Experience Assessment and Prediction for Mobile Networks) - Ref. UMA-CEIATECH-15, and the Spanish Ministry of economic affairs and Digital Transformation and European Union - NextGenerationEU within the framework “Recuperación, Transformación y Resiliencia y el Mecanismo de Recuperación y Resiliencia” - project MAORI, and Univer- sidad de Málaga through the “II Plan Propio de Investigación, Transferencia y Divulgación Científica” This work was possible thanks to the partnership with Metricell Limited to provide a very large dataset of anonymized metrics from real cellular network users. This work has been also funded by: Spanish Ministry of Universities - Ref. FPU20/02863

Infraestructura 5G Standalone para Investigación y Desarrollo

The deployment of 5G infrastructures has been notably addressed during the last years. In contrast, most of the cellular operators are opting for deploying 5G Non- Standalone (NSA), which relies on LTE as anchor technology (signaling, guaranteed coverage...). Nevertheless, 5G NSA is not able to provide all the enhancements that 5G envisions to introduce, including a wide variety of services and use cases. At the University of Ma ́laga, a complete 5G Standanlone (SA) private network has been deployed for research and development purposes. This infrastructure is composed by both indoor and outdoor cells with different equipment, respectively. It enables the use novel technologies such as beamforming to achieve better capacity and coverage, which means higher bandwidths and lower latencies. The aim of this work is to analyze the benefits in terms of transmission bandwidth and latency with reference to a LTE private network. To accomplish this, some tests have been performed over the 5G SA network, providing also some insights about the use of MEC (Multi-access Edge Computing) in 5G.Este trabajo está parcialmente financiado por el programa de “Ayudas para la formación de profesorado universitario” (Ref. FPU20/02863) del Ministerio de Universidades, la beca postdoctoral (Ref. DOC 01154, “Selección de personal investigador doctor convocado mediante Resolución de 21 de mayo de 2020”, PAIDI 2020), y el Ministerio de Asuntos Económicos y Transformación Digital y la Unión Europea - NextGenerationEU, en el marco del Plan de Recuperación, Transformación y Resiliencia y el Mecanismo de Recuperación y Resiliencia bajo el proyecto MAORI. La infraestructura descrita fue concedida mediante la convocatoria de “Ayudas para la adquisición de equipamiento científico-técnico (Plan Estatal I+D+I 2017-2020)”, Ref. EQC2018-005173-P. El trabajo también ha sido parcialmente financiado por la Universidad de Málaga, a través del II Plan Propio de Investigación y Transferencia. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Análisis de Interferencia Cross-Link sobre un escenario 5G mmWave

The use of Time Division Duplex (TDD) has not been fully adopted by operators in LTE networks and its previous generations. In contrast, the fifth generation (5G) is introducing new technical motivations for its use. In order to achieve network flexibility as well as to provide service to every use case, it is necesary to adapt the resources allocated to DL and UL. On the other hand, beamforming techniques require sharing channel state information regularly in both directions. Hence, TDD is a promising option, although it may cause various interference types. The aim of this work is to analyze the Cross-Link Interference (CLI). To do this, a complete scenario simulation has been configured with different conditions, while the signal- to-interference-plus-noise ratio (SINR) has been monitored.Este trabajo está parcialmente financiado dentro del proyecto H2020 LOCUS (grant agreement n. 871249), la Junta de Andalucía y fondos FEDER (Programa Operativo FEDER Andalucía 2014-2020), en los proyectos IDADE-5G (UMA18- FEDERJA-201) y OptiRAN5G (UMA18-FEDERJA-174), y la beca postdoctoral (Ref. DOC_01154, “Selección de personal investigador doctor convocado mediante Resolución de 21 de mayo de 2020”, PAIDI 2020). También ha sido parcialmente financiado por la Universidad de Málaga, a través del I Plan Propio de Investigación y Transferencia. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Posicionamiento 5G con mapas radio incompletos.

Precise positioning will play a key role in future 5G/6G services. The upcoming location-based services drive the necessity of high-precision positioning to indoors. In fingerprinting, which is the most commonly used indoor location algorithm, comprehensive radio maps are essential for a precise localization service and highly influence on the result of the final position of the user. A robust algorithm that supports missing information from the map may improve the robustness and reliability of the localization service. In this work, we compare the performance of fingerprinting and different decision tree (DTR) and Adaboost (DTA and LTA) based regressors in a real 5G scenario with missing information. Additionally, we demonstrate the robustness of the LTA method, which had the highest performance among the tested approaches.Este trabajo se ha realizado en el marco del proyecto Maori (acuerdo de subvención número TSI-063000-2021-53) financiado por la Unión Europea- NextGenerationEU. Además, también ha sido parcialmente financiado por la Universidad de Málaga, Campus de Excelencia Internacional Andalucia Tech