Potentzia domeinuko NOMA 5G sareetarako eta haratago

Tesis inglés 268 p. -- Tesis euskera 274 p.During the last decade, the amount of data carried over wireless networks has grown exponentially. Several reasons have led to this situation, but the most influential ones are the massive deployment of devices connected to the network and the constant evolution in the services offered. In this context, 5G targets the correct implementation of every application integrated into the use cases. Nevertheless, the biggest challenge to make ITU-R defined cases (eMBB, URLLC and mMTC) a reality is the improvement in spectral efficiency. Therefore, in this thesis, a combination of two mechanisms is proposed to improve spectral efficiency: Non-Orthogonal Multiple Access (NOMA) techniques and Radio Resource Management (RRM) schemes. Specifically, NOMA transmits simultaneously several layered data flows so that the whole bandwidth is used throughout the entire time to deliver more than one service simultaneously. Then, RRM schemes provide efficient management and distribution of radio resources among network users. Although NOMA techniques and RRM schemes can be very advantageous in all use cases, this thesis focuses on making contributions in eMBB and URLLC environments and proposing solutions to communications that are expected to be relevant in 6G

AROMA: An adapt-or-reroute strategy for multimedia applications over SDN-based wireless environments

To support new and advanced multimedia-rich applications and services while providing satisfactory user experience, the underlying network infrastructure needs to evolve and adapt. One of the key enabling technologies of the next generation (5G) networks is the integration of Software Defined Networking (SDN) within a heterogeneous wireless environment to enable interoperability and QoS provisioning. Leveraging on the features of the SDN paradigm, it is possible to introduce new solutions to handle the increasing mobile video transmission challenges with strict QoS requirements, such as: low delay, jitter, packet loss, and high bandwidth demands. However, degradation and instability perceived from video traffic makes it difficult to satisfy various end-users. In this context, this paper proposes AROMA, an Adapt-or-reROute strategy for Multimedia Applications over SDN-based wireless environments. AROMA enables QoS provisioning over multimedia-oriented SDN-based WLAN environments. The proposed solution is evaluated using a real experimental test-bed setup

A fairness-driven resource allocation scheme based on weighted interference graph in HetNets

—One of the most important 5G features is their support for heterogeneous networks (HetNets). Complementing the classic macrocell base stations (MBS), femtocell base stations (FBS) are beneficial in terms of extensive coverage, including indoor, and enhancement of capacity. Unfortunately, FBSs performance in 5G HetNets is affected by complex cross-tier and co-tier interferences, causing reduced quality of service (QoS) and unfairness among users. This paper proposes an innovative resource allocation (RA) algorithm for interference mitigation (IM) based on graph coloring techniques to improve QoS and interuser fairness. The proposed algorithm, named Weighted EdgeWeighted Vertex Interference Mitigation (WEWVIM), employs a weight to the directed edge corresponding to the interference strength from nearby base stations (BSs) and a weight to every vertex, indicating the color with the smallest interference or higher transmission rate. A region of interest (ROI) is formed to find the interfering BSs. Simulation results show that WEWVIM outperforms existing schemes in terms of fairness and QoS, including throughput, packet loss ratio (PLR), delay, and jitter. Index Terms—HetNets, Graph Coloring, Interference Mitigation, 5G, QoS, Resource Allocatio

Implementation and performance evaluation of a MIMO-VLC system for data transmissions

The ever-increasing streaming culture of large amounts of data and the need for faster and reliable methods of data transfer has created a space and market for new communication technologies such as Visible Light Communication (VLC). However, the integration of VLC into next generation networks is challenging due to the drawbacks of the technology in terms of atmospheric absorption, shadowing, beam dispersion, etc. One way to overcome some of the challenges is to make use of the multiple input multiple output (MIMO) technique which involves the transmission of data in parallel from multiple sources, increasing the data rate. This paper implements and provides a comprehensive evaluation of a MIMO-VLC system for data transmission. A real experimental test-bed is setup to test the performance of the MIMO-VLC system under various conditions such as distance from the source based on luminous flux, ambient lighting, output power, etc. Additionally, subjective tests are carried out to assess the quality of an audio MIMO VLC link as perceived by the user. The results are compared with the results of a Single Input Single Output (SISO)-VLC system

Point-to-Multipoint Services on Fifth-Generation Mobile Networks

[ES] Esta disertación cubre el estado del arte en LTE eMBMS Release 14, también conocido como Enhanced Television Services (ENTV). ENTV trajo un conjunto de mejoras, tanto a nivel radio como a nivel de núcleo, que transformó a eMBMS en un estándar de televisión terrestre completo. La última versión de esta tecnología se denomina LTE-based 5G Broadcast; pero no usa New Radio ni el núcleo 5G. Para proveer una solución nativa 5G de servicios punto-a-multipunto, hubo investigación en entornos acad\'emicos y colaboraciones público-privada. La iniciativa más notable en este aspecto fue el proyecto del Horizon 2020 5G-Xcast, que transcurrió de 2017 a 2019. 5G-Xcast produjo varias soluciones a nivel de arquitectura, desde la perspectiva de provisión de contenidos, nuevas funciones de red interoperables con el núcleo 5G, hasta modificaciones a la interfaz aire basada en New Radio. Los hallazgos del proyecto están descritos en esta tesis. La tesis incluye dos ejemplos de eMBMS aplicados a verticales diferentes, una para el uso de eMBMS en entornos industriales, y otra presentando eMBMS como un sistema SAP. Incluir servicios punto-a-multipunto como un modo adicional celular trae algunos desafíos, como ya mostró la estandarización de eMBMS: las redes de radiodifusión terrestre y las redes celulares son muy distintas entre ellas. Encontrar una forma de onda viable para ambas infraestructuras es complejo. Esta tesis ofrece un punto de vista distinto al problema: un escenario de colaboración entre cadenas televisivas y operadores móviles, donde la infraestructura de radiodifusión y móvil son compartidas. Este concepto se ha definido como Convergence of Terrestrial and Mobile Networks. Las tecnologías elegidas para converger son ATSC 3.0 y 5G, usando el Advanced Traffic Steering, Switching and Splitting (ATSSS). ATSSS está compuesto de una serie de procedimientos, interfaces, funciones de red, para permitir el uso compartido de un acceso 3GPP con uno non-3GPP, como Wi-Fi. Sin embargo, el uso de ATSSS para juntar radiodifusión y celular no es trivial, ya que ATSSS no fue dise\~{n}ado para enlaces radio unidireccionales como ATSC 3.0. Estas limitaciones son descritas en detalle, y una propuesta para solventarlas tambi\'en está incluida. La solución se basa en Quick UDP Internet Connections (QUIC), y se usa como ejemplo para la provisión de Convergent Services (File Repair y Video Offloading). La tesis concluye con una descripción de Release 17 5MBS, con los nuevos conceptos introducidos. 5MBS es capaz de cambiar entre unicast, multicast y broadcast; dependiendo del servicio, la ubicación geográfica de los usuarios, y las capacidades de la infraestructura móvil involucradas. Para evaluar 5MBS, se ha realizado un estudio de prestaciones, basado en comunicaciones multicast dentro del núcleo de red 5G. Este prototipo 5MBS forma parte del laboratorio VLC Campus 5G, y utiliza el software comercial Open5GCore como base del desarrollo. El modelo de sistema para la experimentación esta formado por un servidor de vídeo, que se conecta al Open5GCore y a las funciones de red mejoradas con funcionalidades 5MBS. Estas funciones de red envían el contenido mediante punto-a-multipunto a un entorno radio y terminales simulados. Los resultados obtenidos resaltan el objetivo principal de la tesis: las comunicaciones punto-a-multipunto son una solución escalable para el envío de contenido multimedia en directo.[CA] Aquesta dissertació cobreix capdavanter en LTE eMBMS Release 14, també conegut com Enhanced Television Services (ENTV). ENTV va portar un conjunt de millores, tant a nivell de ràdio com a nivell de nucli, que va transformar el eMBMS en un estàndard de televisió terrestre complet. La última versió d'aquesta tecnologia es denomina LTE-based 5G Broadcast; però no fa servir New Ràdio ni el nucli 5G. Per a proveir una solució nativa 5G de serveis punt-a-multipunt, va haver-hi investigació en entorns acadèmics i col·laboracions pública i privada. La iniciativa més notable en aquest aspecte va ser el projecte del Horizon 2020 5G-Xcast, que va transcórrer del 2017 a 2019. 5G-Xcast va produir diverses solucions a nivell d'arquitectura, des de la perspectiva de provisió de continguts, noves funcions de xarxa interoperables amb el nucli 5G, fins a modificacions a la interfície aire basada en New Radio. Les troballes del projecte estan descrits en aquesta tesi. La tesi inclou dos exemples de eMBMS aplicats a verticals diferents, una per a l'ús de eMBMS en entorns industrials, i una altra presentant eMBMS com un sistema SAP. Incloure serveis punt-a-multipunt com una manera addicional cel·lular duu alguns desafiaments, com ja va mostrar l'estandardització de eMBMS: les xarxes de radiodifusió terrestre i les xarxes cel·lulars són molt diferents entre elles. Trobar una forma d'ona viable per a totes dues infraestructures és complex. Aquesta tesi ofereix un punt de vista diferent al problema: un escenari de col·laboració entre cadenes televisives i operadors mòbils, on la infraestructura de radiodifusió i mòbil són compartides. Aquest concepte s'ha definit com Convergence of Terrestrial and Mobile Networks. Les tecnologies triades per a convergir són ATSC 3.0 i 5G, usant el Advanced Traffic Steering, Switching and Splitting (ATSSS). ATSSS està compost d'una sèrie de procediments, interfícies, funcions de xarxa, per a permetre l'ús compartit d'un accés 3GPP amb un non-3GPP, com a Wi-Fi. No obstant això, l'ús de ATSSS per a adjuntar radiodifusió i cel·lular no és trivial, ja que ATSSS no va ser dissenyada per a per a enllaços ràdio unidireccionals com ATSC 3.0. Aquestes limitacions són descrites detalladament, i una proposta per a solucionar-les també està inclosa. La solució es basa en Quick UDP Internet Connections (QUIC), i s'usa com a exemple per a la provisió de Convergent Services (File Repair i Vídeo Offloading). La tesi conclou amb una descripció de Release 17 5MBS, amb els nous conceptes introduïts. 5MBS és capaç de canviar entre unicast, multicast i broadcast; depenent del servei, la ubicació geogràfica dels usuaris, i les capacitats de la infraestructura mòbil involucrades. Per a avaluar 5MBS, s'ha realitzat un estudi de prestacions, basat en comunicacions multicast dins del nucli de xarxa 5G. Aquest prototip 5MBS forma part del laboratori VLC Campus 5G, i utilitza el programari comercial Open5GCore com a base del desenvolupament. El model de sistema per a l'experimentació està format per un servidor de vídeo, que es connecta al Open5GCore i a les funcions de xarxa millorades amb funcionalitats 5MBS. Aquestes funcions de xarxa envien el contingut mitjançant punt-a-multipunt a un entorn ràdio i terminals simulats. Els resultats obtinguts ressalten l'objectiu principal de la tesi: les comunicacions punt-a-multipunt són una solució escalable per a l'enviament de contingut multimèdia en directe.[EN] This dissertation covers the state-of-the-art in LTE eMBMS Release 14, also known as Enhanced Television Services (ENTV). ENTV provided a suite of radio and core enhancements that made eMBMS into a viable terrestrial broadcast standard. The latest iteration of this technology is known as LTE-based 5G Broadcast; even though it is not New Radio or 5G Core based. To bridge this gap, research efforts by academia, public and private enterprises evaluated how to provide a 5G-based solution for point-to-multipoint services. The most notable effort in this regard is the Horizon 2020 project 5G-Xcast, which ran from 2017 to 2019. 5G-Xcast provided several architectural solutions, from the content delivery perspective down to air interface specifics; providing new waveforms based on New Radio and Network Functions interoperable with a Release 15 5G Core. The findings are summarized in this thesis. Two examples of eMBMS applied to different verticals are included in the thesis, one for the use of eMBMS in industrial environments, and the other using eMBMS as a PWS technology. Providing point-to-multipoint services as another cellular service poses some problems, as the standardization process of eMBMS showed: the broadcast infrastructure is different than the cellular one. Having a waveform that is suited for both scenarios is a difficult endeavour. The thesis provides a new perspective into this problem: Having existing Terrestrial Broadcast standards and infrastructure be the point-to-multipoint solution of 5G, where mobile operators and broadcasters collaborate together. This is defined in the dissertation as Convergence of Terrestrial and Mobile Networks. The technologies chosen to be converged together were ATSC 3.0 and 5G; using the existing Release 16 framework known as Advanced Traffic Steering, Switching and Splitting (ATSSS). ATSSS is a series of procedures, interfaces, new Network Functions, to allow the joint use of a 3GPP Access Network alongside a non-3GPP one, like Wi-Fi. However, the use of ATSSS for cellular plus broadcast brings challenges, as the ATSSS technology was not designed to be used with a unidirectional access network like ATSC 3.0. These limitations are described in detail, and an architectural proposal that overcomes the limitations is proposed. This solution is based on Quick UDP Internet Connections (QUIC), and how to provide Convergent Services (i.e File Repair and Video Offloading) is shown. The thesis concludes with a description of Release 17 5MBS, including the new concepts introduced. 5MBS features the capacity of switching between unicast, multicast and broadcast; depending on the service addressed, the geographical location of the users, and the capability of the RAN infrastructure targeted. In order to evaluate 5MBS, a performance study of the use of multicast inside the 5G Core has been carried out. The 5MBS prototype was developed as part of the VLC Campus 5G laboratory, using the commercial software Open5GCore which provides the libraries and Network Functions to deploy your own 5G Private Network in testing environments. The system model of the experiment is formed by a video server, connected to the Open5GCore and the 5MBS enhanced functions; which will deliver the content to an emulated RAN environment hosting virtual gNBs and devices. The results obtained reinforce the objective of the thesis, positioning point-to-multipoint as a scalable way to deliver live content.Research projects: 5G-Xcast: Broadcast and Multicast Communication Enablers for the Fifth-Generation of Wireless Systems (H2020 No 761498); 5G-TOURS: SmarT mObility, media and e-health for toURists and citizenS (H2020 No 856950); FUDGE-5G: FUlly DisinteGrated private nEtworks for 5G verticals (H2020 No 957242).Barjau Estevan, CS. (2022). Point-to-Multipoint Services on Fifth-Generation Mobile Networks [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/19140

Estimation of the QoE for video streaming services based on facial expressions and gaze direction

As the multimedia technologies evolve, the need to control their quality becomes even more important making the Quality of Experience (QoE) measurements a key priority. Machine Learning (ML) can support this task providing models to analyse the information extracted by the multimedia. It is possible to divide the ML models applications in the following categories: 1) QoE modelling: ML is used to define QoE models which provide an output (e.g., perceived QoE score) for any given input (e.g., QoE influence factor). 2) QoE monitoring in case of encrypted traffic: ML is used to analyze passive traffic monitored data to obtain insight into degradations perceived by end-users. 3) Big data analytics: ML is used for the extraction of meaningful and useful information from the collected data, which can further be converted to actionable knowledge and utilized in managing QoE. The QoE estimation quality task can be carried out by using two approaches: the objective approach and subjective one. As the two names highlight, they are referred to the pieces of information that the model analyses. The objective approach analyses the objective features extracted by the network connection and by the used media. As objective parameters, the state-of-the-art shows different approaches that use also the features extracted by human behaviour. The subjective approach instead, comes as a result of the rating approach, where the participants were asked to rate the perceived quality using different scales. This approach had the problem of being a time-consuming approach and for this reason not all the users agree to compile the questionnaire. Thus the direct evolution of this approach is the ML model adoption. A model can substitute the questionnaire and evaluate the QoE, depending on the data that analyses. By modelling the human response to the perceived quality on multimedia, QoE researchers found that the parameters extracted from the users could be different, like Electroencephalogram (EEG), Electrocardiogram (ECG), waves of the brain. The main problem with these techniques is the hardware. In fact, the user must wear electrodes in case of ECG and EEG, and also if the obtained results from these methods are relevant, their usage in a real context could be not feasible. For this reason, my studies have been focused on the developing of a Machine Learning framework completely unobtrusively based on the Facial reactions

Implementing Deep Learning Techniques in 5G IoT Networks for 3D Indoor Positioning: DELTA (DeEp Learning-Based Co-operaTive Architecture)

In the near future, the fifth-generation wireless technology is expected to be rolled out, offering low latency, high bandwidth and multiple antennas deployed in a single access point. This ecosystem will help further enhance various location-based scenarios such as assets tracking in smart factories, precise smart management of hydroponic indoor vertical farms and indoor way-finding in smart hospitals. Such a system will also integrate existing technologies like the Internet of Things (IoT), WiFi and other network infrastructures. In this respect, 5G precise indoor localization using heterogeneous IoT technologies (Zigbee, Raspberry Pi, Arduino, BLE, etc.) is a challenging research area. In this work, an experimental 5G testbed has been designed integrating C-RAN and IoT networks. This testbed is used to improve both vertical and horizontal localization (3D Localization) in a 5G IoT environment. To achieve this, we propose the DEep Learning-based co-operaTive Architecture (DELTA) machine learning model implemented on a 3D multi-layered fingerprint radiomap. The DELTA begins by estimating the 2D location. Then, the output is recursively used to predict the 3D location of a mobile station. This approach is going to benefit use cases such as 3D indoor navigation in multi-floor smart factories or in large complex buildings. Finally, we have observed that the proposed model has outperformed traditional algorithms such as Support Vector Machine (SVM) and K-Nearest Neighbor (KNN)

Mission-Critical Communications from LMR to 5G: a Technology Assessment approach for Smart City scenarios

Radiocommunication networks are one of the main support tools of agencies that carry out actions in Public Protection & Disaster Relief (PPDR), and it is necessary to update these communications technologies from narrowband to broadband and integrated to information technologies to have an effective action before society. Understanding that this problem includes, besides the technical aspects, issues related to the social context to which these systems are inserted, this study aims to construct scenarios, using several sources of information, that helps the managers of the PPDR agencies in the technological decisionmaking process of the Digital Transformation of Mission-Critical Communication considering Smart City scenarios, guided by the methods and approaches of Technological Assessment (TA).As redes de radiocomunicações são uma das principais ferramentas de apoio dos órgãos que realizam ações de Proteção Pública e Socorro em desastres, sendo necessário atualizar essas tecnologias de comunicação de banda estreita para banda larga, e integra- las às tecnologias de informação, para se ter uma atuação efetiva perante a sociedade . Entendendo que esse problema inclui, além dos aspectos técnicos, questões relacionadas ao contexto social ao qual esses sistemas estão inseridos, este estudo tem por objetivo a construção de cenários, utilizando diversas fontes de informação que auxiliem os gestores destas agências na tomada de decisão tecnológica que envolve a transformação digital da Comunicação de Missão Crítica considerando cenários de Cidades Inteligentes, guiado pelos métodos e abordagens de Avaliação Tecnológica (TA)

Neural network design for intelligent mobile network optimisation

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe mobile networks users’ demands for data services are increasing exponentially, this is due to two main factors: the first is the evolution of smart phones and their application, and the second is the emerging new technologies for internet of things, smart cities…etc, which keeps pumping more data into the network; ‘though most of the data routed in the current mobile network is non-live data’. This increasing of demands arise the necessity for the mobile network operators to keep improving their network to satisfy it, this improvement takes place via adding hardware or increasing the resources or a combination of both. The radio resources are strictly limited due to spectrum licensing and availability, therefore efficient spectrum utilization is a major goal to be achieved for both network operators and developers. Simultaneous and multiple channel access,and adding more cells to the network are ways used to increase the data exchanged between the network nodes. The current 4G mobile system is based on the Orthogonal Frequency Division Multiple Access (OFDMA) for accessing the medium and the intercell interference degrades the link quality at the cell edge, with the introduction of heterogeneity concept to the LTE in Release 10 of the 3GPP the handover process became even more complex. To mitigate the intercell interference at the cell edge, coordinated multipoint and carrier aggregation techniques are utilized for dual connectivity. This work is focused on designing and proposing enhancing features to improve network performance and sustainability, these features comprises of distributing small cells for data only transmission, handover schemes performance evaluation at cell edge with dual connectivity, and Artificial Intelligence technology for balancing and prediction. In the proposed model design the data and controls of the Small eNodeB (SeNodeB) are processed at the network edge using a Mobile Edge Computing (MEC) server and the SeNodeBs are used to boost services provided to the users, also the concept of caching data has been investigated, the caching units where implemented in different network levels. The proposed system and resource management are simulated using the OPNET modeller and evaluated through multiple scenarios with and without full load, the UE is reconfigured to accommodate dual connectivity and have two separate connections for uplink and downlink, while maintaining connection to the Macro cell via uplink, the downlink is dedicated for small cells when content is requested from the cache. The results clearly show that the proposed system can decrease the latency while the total throughput delivered by the network has highly improved when SeNodeBs are deployed in the system, rising throughput will incur the rise of overall capacity which leads to better services being provided to the users or more users to join and benefit from the network. Handover improvement is also considered in this work, with the help of two Artificial Intelligence (AI) entities better handover performance are achieved. Balanced load over the SeNodeBs results in less frequent handover, the proposed load balancer is based on artificial neural network clustering model with self-organizing map as a hidden layer, it’s trained to forecast the network condition and learn to reduce the number of handovers especially for the UEs at the cell edge by performing only necessary ones, and avoid handovers to the Macro cell for the downlink direction. The examined handovers concern the downlinks when routing non live video stored at the small cell’s cache, and a reduction in the frequent handovers was achieved when running the balancer. Keep revolving in the handover orbit, another way to preserve and utilize network resources is by predicting the handovers before they occur, and allocate the required data in the target SeNodeB, the predictor entity in the proposed system architecture combines the features of Radial Basis Function Neural Network and neural network time series tool to create and update prediction list from the system’s collected data and learn to predict the next SeNodeB to associate with. The prediction entity is simulated using MATLAB, and the results shows that the system was able to deliver up to 92% correct predictions for handovers which led to overall throughput improvement of 75%