REDUCCIÓN DEL COSTE COMPUTACIONAL DE LA INFERENCIA DE CONTEXTO BAYESIANA MEDIANTE EL USO DE RANGOS DE VALORES DINÁMICOS

This paper shows how to reduce evaluation time for context inference. Probabilistic Context Inference has proven to be more powerful and better adapted to the challenges of the physical reality with uncertain or missing information. As the inference complexity is very high, the complexity of the to be evaluated rule (representing a share of the real world) should be reduced as far as possible. Therefore we present an approach to select only relevant values of context types and to adapt this selection during its usage time. In an evaluation we show that with only a few evaluations of the reduced inference rules the reduction costs will have amortized and the system brings significant benefit to context aware computing

A Semi-Supervised Location-Aware Anomaly Detection Method for Ultra-Dense Indoor Scenarios.

Over the past few years, indoor cellular deployments have been on the rise. These scenarios are characterized by their user density and fast-changing conditions, thus, being prone to failures. Moreover, the steady development of indoor and outdoor positioning techniques is expected to provide a reliable source of information. Thus, the availability of user location is being considered to be a key enabler to improve the resilience and performance of automatic failure management and optimization techniques. Taking this into consideration, the present work proposes a semi-supervised location-aware anomaly detection method for the management of failures such as cell outages and interference problems.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

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

Análisis del efecto del número de beams sobre un escenario 5G

5G has been presented as the most revolutionary generation in the mobile network paradigm. With regard to the RAN part, the main achieved improvements in comparison with its predecessor are based on the use of mmWaves. To overcome the high propagation losses that are inherent to mmWaves, beamforming scheme usage becomes essential. In this scope, the aim of this paper is to provide a first approach regarding the effect of the beamforming configuration in these radio networks. To do so, a complete scenario has been simulated in ns-3, enabling the evaluation of the signal-to-interference-plus- noise ratio (SINR) received by a UE under different number of configured beams.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Diagnosis automática con 5G para entornos de emergencia

Emergency communications are a fundamental aspect for any community, becoming more necessary year after year. This fact, together with the continuous advance of mobile network technologies, enables increasingly more reliable and faster communications in critical situations. The aim of this work is to provide a diagnostic system to detect the specific failures that occur in a mobile network in an emergency situation. In the same way, the proposed methodology is also capable of providing the most suitable solution to mitigate the effects that the disaster or emergency has caused in the network.Este trabajo ha sido financiado parcialmente por la Unión Europea en el marco del proyecto ’Massive AI for the Open Radio beyond 5G/6G (MAORI)’ de la Next Generation EU, .También parcialmente financiado a través del II Plan Propio de Investigación y Transferencia de la Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech

A Framework to boost the potential of networkin- a-box solutions

The expected heterogeneous connectivity provided by the fifth generation mobile network (5G) implies a huge revolution in the telecommunication field. Here, virtualisation and software implementation of network elements have been positioned as a key elements for this revolution. At the same time and as a consequence of the evolution of these two paradigms, network-in-a-box solutions have also emerged as a potential way in the deployment of networks, offering a portable infrastructure. Here, this work presents a framework for easing the management tasks of the network-in-a-box devices, allowing abstracting the hardware and software implementation of these kind of solutions. We provide an experimental validation of the framework through the deployment of a portable cellular network. Besides, a Cloud Gaming service is launched on this scenario, showing the versatility and strengths that the framework provides to these novel solutions.This work has been partially funded by “Ministerio de Asuntos Económicos y transformación digital” (red.es, “Piloto 5G Andalucía, Caso 31 OpenRAN”), by “Ministerio de Ciencia e Innovación” (grant FPU19/04468), and by Junta de Andalucía and European Regional Development Fund (ERDF) through AECMA-5G (UMA-CEIATECH-14) and post-doctoral grant (DOC01154, PAIDI 2020

5G in airports: challenges and use cases.

5G is the new generation of cellular communications that aims to provide high-throughput high-reliability connectivity to greatly diversified scenarios. With this objective, it shall act as a viable solution for environments as complex as an airport terminal, whose daily work cycle includes a wide range of diversified activities. As such, in this paper, 5G capacities are assessed, identifying those airport processes that can benefit from its application. From the proposed use cases, the monitoring of luggage trolleys is identified as a key use case that poses a problematic that is usually approached in a very inefficient way, due to the lack of information about the position and state of the trolleys. In this sense, a management system for the luggage trolleys using NarrowBand Internet of Things (NB-IoT) and Bluetooth Low Energy (BLE) is proposed.This work has been partially funded by: Junta de Andalucía and EDRF in the framework of 5G-SCARF: 5G Smart Communications for the AiRport of the Future (Ref. UMACEIATECH- 17) project, Ministerio de Asuntos Económicos y Transformación Digital and European Union – NextGenerationEU within the framework “Recuperación, Transformación y Resiliencia y el Mecanismo de Recuperación y Resiliencia” under the project MAORI and Universidad de Málaga through the “II Plan Propio de Investigación, Transferencia y Divulgación Científica”. The authors are grateful to Aertec Solutions’ Airport Area for their support and collaboration in this work

ML-based network management framework for XR services.

This work presents a novel framework designed for the management of XR (Extended Reality) services for B5G/6G network paradigms. These networks will enable its near-future deployment to change the concept of the XR experiences known at this moment. Our proposed framework powered by ML (Machine Learning) consists of the measurement and estimation of metrics based on network-accessible information, and a proof of concept of network optimization. The latter is based on the use of KQI (Key Quality Indicators) to tune the performance of XR services. This in conjunction with ML approaches, can offer additional levels of intelligence to networks. To validate this, a 360-video service has been selected as a use case to provide a proof of concept of the performance, utility, and novelty of this work.This work has been partially funded by: Ministerio de Asuntos Económicos y Transformación Digital and European Union - NextGenerationEU within the framework “Recuperación, Transformación y Resiliencia y el Mecanismo de Recuperación y Resiliencia” under the project MAORI, and Universidad de Málaga through the “II Plan Propio de Investigación, Transferencia y Divulgación Científica”. This work has been also supported by Junta de Andalucía through Secretaría General de Universidades, Investigación y Tecnología with predoctoral grant (Ref. PREDOC_01712) as well as by Ministerio de Ciencia y Tecnología through grant FPU19/04468. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech