Thèses sur le sujet « Beyond 5G Networks »

Massive multiple input multiple output (MIMO) is a promising 5G and beyond5G wireless access technology that can provide huge throughput, compared with the current technology, in order to satisfy some requirements for the future generations of wireless networks. The research described in this thesis proposes the design of some applications of the massive MIMO technology that can be implemented in order to increase the spectral efficiency per cell of the future wireless networks through a simple and low complexity signal processing. In particular, massive MIMO is studied in conjunction with two other topics that are currently under investigation for the future wireless systems, both in academia and in industry: the millimeter wave frequencies and the distributed antenna systems. The first part of the thesis gives a brief overview on the requirements of the future wireless networks and it explains some of the mathematical tools used in the current massive MIMO literature. Then, an overview on the differences between massive MIMO techniques at the conventional cellular frequencies and at millimeter wave frequencies is presented and exhaustively discussed. Six key basic differences are pinpointed, along with the implications that they have on the architecture and algorithms of the communication transceivers and on the attainable performance in terms of reliability and multiplexing capabilities. Subsequently, “doubly massive MIMO” systems at millimeter wave frequencies are introduced, i.e., systems with a large number of antennas at both the transmitter and the receiver. For complexity reasons and energy consumption issues, fully digital pre-coding and post-coding structures may turn out to be unfeasible, and thus suboptimal structures, making use of simplified hardware and a limited number of radio-frequency chains, have been investigated. A comparative assessment of several suboptimal pre-coding and post-coding structures with large number of antennas is discussed. Numerical results show that fullydigital beamformers may actually achieve a larger energy efficiency than lowercomplexity solutions, as well as that low-complexity beam-steering purely analog beamforming may in some cases represent a good performance-complexity trade-off solution. Finally, the thesis focuses on the recently introduced cell-free massive MIMO architecture, wherein a very large number of distributed access points, connected to a central processing unit, simultaneously and jointly serve a much smaller number of mobile stations. It contrasts the originally proposed formulation of cell-free massive MIMO with a user-centric approach wherein each mobile station is served only by a limited number of access points. Exploiting the framework of successive lower-bound maximization, this thesis also proposes and analyzes two power allocation strategies aimed at maximizing the throughput and the fairness of these systems. Additionally, advanced signal processing techniques, to improve the performance of the user-centric approach both in uplink and in downlink, are proposed. The proposed schemes can be implemented locally, i.e., with no need to exchange information with the central processing unit. Numerical results show that the user-centric approach, which requires smaller backhaul overhead and it is more scalable than the cell-free massive MIMO deployment, also achieves generally better performance than the cell-free massive MIMO approach for the vast majority of the users in the system, especially on the uplink. Regarding the proposed advanced signal processing techniques, the results show that they provide remarkable performance improvements with respect to the competing alternatives.

Massive Multiple-Input-Multiple-Output (MIMO) is a recent technlogy that will be exploited for 5G and beyond-5G wireless network due to the constraints given by the future wireless networks, such as low latency and high spectral efficiency. In this thesis, MIMO systems have been taken into account in order to study two different network architectures. The former is called Cell-Free (CF), and it has been studied at millimeter Wave (mmWave) and microwave frequencies, and the latter is called Distributed Multiple Input Multiple Output (D-MIMO) for factory automation. The first chapter of this thesis gives an overview of massive MIMO, so why there is the need to exploit this technology and gives some mathematical concept. In the second chapter the CF at mmwave frequencies has been studied. The CF is a recent network architecture, in order to alleviate the cell-edge problem and thus increase the system performance of unlucky users that happen to be located very far from their serving Access Point (AP). In this architecture a large number of distributed APs, connected to a central processing unit (CPU), simultaneously and jointly serve a much smaller number of mobile Station (MS) or users. Both APs and users are equipped with multiple antennas. Then, it has been analyzed an architecture that generalizes the CF, the so called User-centric (UC), where each AP has to serve only a limited number of users. A power control algorithm has been introduced by resorting a method called successive lower bound maximization, aimed at maximizing the sum-rate and the energy efficiency. At mmwave, a lot of antennas can be employed, this means that there is the need of using hybrid architecture at each AP in order to reduce complexity and cost by using a small number of radio frequency (RF) chains. With CF or UC, channel estimation and beamforming are locally evaluated, reducing the traffic load on the backhaul network. So, a comparison between a fully digital (FD) and hybrid (HY) architecture will be shown. What it is possible to anticipate is that the FD architecture provides better performances than the hybrid one. In the numerical results, the performances in term of energy efficiency and sum-rate on Downlink and Uplink, with uniform and optimal power allocation and with a fully digital and hybrid architectures will be addressed. Then, this thesis also focuses on the comparison between D-MIMO and CF architectures for factory automation, at microwave frequencies. In this case, communications between actuators (ACs) and APs inside an industrial scenario is considered by adopting those different communication systems. Then, different transmission modes are taken into account, Joint transmission joint transmission (JT), Cell-Free transmission (CFT), single AP transmission (SAT), and User-centric transmission (UCT). In SAT mode each AC is served by only one AP. Even for this scenario a power control rule has been taken into account. In the end, in numerical section, it has been shown the performances in terms of SINR and achievable rate, evaluated with the finite block length capacity (FBLC) formula, when different transmission modes and beamformers are employed, and moreover the improvement given by the use of a power control.

L’augmentation exponentielle des équipements d’utilisateurs sans fil (UEs) et des services des réseaux associés aux déploiements actuels de cinquième génération (5G) pose plusieurs défis de conception sans précédent qui doivent être résolus avec l’avènement des futurs réseaux au-delà de la 5G. Plus précisément, la demande croissante de débits de données élevés ainsi que la nécessité de desservir un grand nombre d’appareils hétérogènes, allant des téléphones mobiles classiques aux objets connectés formant l’internet des objets (IoT), motivent l’étude de nouveaux schémas de traitement et de transmission du signal. À cet égard, les sorties multiples massives à entrées multiples (massive MIMO) sont une technologie d’accès bien établie, qui permet de desservir plusieurs dizaines d’UEs en utilisant lesmêmes ressources temps-fréquence au moyen de techniques de formation de faisceau hautement directionnelles. Cependant, le massive MIMO présente des problèmes d’évolutivité dans les scénarios accès massif où la population UE est composée d’un grand nombre de périphériques hétérogènes. En effet, si la disponibilité d’un grand nombre d’antennes dans les émetteurs-récepteurs massive MIMO apporte des gains de performances substantiels, elle augmente également considérablement la surcharge et la complexité du système. Plus précisément, la dimensionnalité élevée des canaux nécessite l’allocation de ressources temps-fréquence considérables pour acquérir les informations d’état de canal (CSI) et se traduit par de grandes opérations matricielles pour construire des précodeurs/décodeurs. De plus, dans le contexte de communications de multidiffusion comme, par exemple, la mise en cache périphérique sans fil ou la diffusion de messages critiques pour la mission, les techniques d’antennes multiples conventionnelles présentent des taux de disparition lorsque le nombre d’UEs augmente même dans le régime d’antenne massif. Enfin, le grand nombre de chaînes de radiofréquences (RF) associées aux émetteurs-récepteurs massive MIMO, qui sont utilisés pour contrer les pertes de propagation dans des environnements difficiles tels que, par exemple, à des fréquences d’ondes millimétriques (mmWave), se heurte au budget de puissance limité des appareils IoT. Dans cette thèse, nous proposons de nouvelles méthodes à antennes multiples évolutives pour l’amélioration des performances dans les scénarios d’intérêt susmentionnés. Plus précisément, nous décrivons le rôle fondamental joué par le CSI statistique qui peut être mis à profit pour réduire à la fois la complexité et la surcharge pour l’acquisition de CSI et pour la suppression des interférences multi-utilisateurs. En effet, lorsque les UEs sont équipés au moins de duex antennes, leurs propriétés de sélectivité spatiale peuvent être exploitées pour imposer une orthogonalité statistique parmi les transmissions interférentes. De plus, nous exploitons les communications de périphérique à périphérique (D2D) pour surmonter le goulot d’étranglement fondamental de la multidiffusion conventionnelle. En particulier, nous exploitons les capacités de précodage d’un émetteur multi-antennes pour sélectionner soigneusement les UEs dans des conditions de canal favorables, qui à leur tour agissent comme des relais opportunistes et retransmettent le message via les liaisons D2D. Enfin, dans le cadre des communications mmWave, nous explorons les avantages des surfaces intelligentes reconfigurables (RISs) récemment proposées, qui sont un catalyseur clé de l’innovation grâce à leur structure intrinsèquement passive qui permet de contrôler l’environnement de propagation et de contrer efficacement les pertes de propagation. En particulier, nous utilisons la formation de faisceaux passive au niveau du RIS, c’est-à-dire sans aucune dépense d’énergie significative, ainsi que la formation de faisceaux active conventionnelle au niveau de l’émetteur pour augmenter considérablement les performances du réseau
The exponential increase of wireless user equipments (UEs) and network services associated with current 5G deployments poses several unprecedented design challenges that need to be addressed with the advent of future beyond-5G networks and novel signal processing and transmission schemes. In this regard, massive MIMO is a well-established access technology, which allows to serve many tens of UEs using the same time-frequency resources. However, massive MIMO exhibits scalability issues in massive access scenarios where the UE population is composed of a large number of heterogeneous devices. In this thesis, we propose novel scalable multiple antenna methods for performance enhancement in several scenarios of interest. Specifically, we describe the fundamental role played by statistical channel state information (CSI) that can be leveraged for reduction of both complexity and overhead for CSI acquisition, and for multiuser interference suppression. Moreover, we exploit device-to-device communications to overcome the fundamental bottleneck of conventional multicasting. Lastly, in the context of millimiter wave communications, we explore the benefits of the recently proposed reconfigurable intelligent surfaces (RISs). Thanks to their inherently passive structure, RISs allow to control the propagation environment and effectively counteract propagation losses and substantially increase the network performance

: The increased interest in traffic-intensive applications such as High Definition (HD) video, augmented reality, and 3-D visualization is expected to result in higher network traffic. Such higher-fold traffic growth requires a significant paradigm shift in implementing upcoming 5G technology so that the user requests can be accommodated at the core network without causing a bottleneck. Emerging mobile content caching techniques can efficiently relieve overloaded network by caching popular content at intermediate nodes and user devices. Its efficacy, however, lies in the intelligent caching of popular files. To better deploy caching, a heterogeneous caching architecture is proposed that supports comprehensive cooperation. We propose three cooperative caching schemes in cellular networks, D2D networks, and cross-tier networks. Caching decisions are made by considering the content popularity, the device distribution, the transmission method, and the caching capability. Furthermore, we investigate a multi-association-based model in which a user associates with multiple caching entities to retrieve its requested content. We then present an agglomerative hierarchical clustering algorithm for setting up users' preferences and grouping them into the same clusters based on the similarity of their requests. Stochastic geometry has been used to model and analyze different coverage scenarios. Gains obtained are quantified in terms of coverage probability, cache hit probability, and delay through numerical and network simulations. Results show that the coverage probability achieved is 40% higher than the compared method. On the other hand, the cache hit probability increases to nearly 90% after clustering with the proposed method. The delay performance outperforms a popularity-based caching scheme and results in a 75% decrease in delay; however, the network's energy consumption is compromised for this purpose.

As mobile networks continue to evolve, two major problems have always existed that greatly affect the quality of service that users experience. These problems are (1) efficient resource management for users at the edge of the network and those in a network coverage hole. (2) network coverage such that improves the quality of service for users while keeping the cost of deployment very low. In this study, two novel algorithms (Collaborative Resource Allocation Algorithm and Memetic-Bee-Swarm Site Location-Allocation Algorithm) are proposed to solve these problems. The Collaborative Resource Allocation Algorithm (CRAA) is inspired by lending and welfare system from the field of political economy and developed as a Market Game. The CRAA allows users to collaborate through coalition formation for cell edge users and users with less than the required Signal-to-Noise-plus-Interference-Ratio to transmit at satisfactory Quality of Service, which is a result of the payoff, achieved and distributed using the Shapley value computed using the Owens Multi Linear Extension function. The Memetic-Bee-Swarm Site Location-Allocation Algorithm (MBSSLAA) is inspired by the behaviour of the Memetic algorithm and Bee Swarm Algorithm for site location. Series of System-level simulations and numerical evaluations were run to evaluate the performance of the algorithms. Numerical evaluation and simulations results show that the Collaborative Resource Allocation Algorithm compared with two popular Long Term Evolution-Advanced algorithms performs higher in comparison when assessed using throughput, spectral efficiency and fairness. Also, results from the simulation of MBSSLAA using realistic network design parameter values show significant higher performance for users in the coverage region of interest and signifies the importance of the ultra-dense small cells network in the future of telecommunications’ services to support the Internet of Things. The results from the proposed algorithms show that following from the existing solutions in the literature; these algorithms give higher performance than existing works done on these problems. On the performance scale, the CRAA achieved an average of 30% improvement on throughput and spectral efficiency for the users of the network. The results also show that the MBSSLAA is capable of reducing the number of small cells in an ultra-dense small cell network while providing the requisite high data coverage. It also indicates that this can be achieved while maintaining high SINR values and throughput for the users, therefore giving them a satisfactory level of quality of service which is a significant requirement in the Fifth Generation network’s specification.

L'émergence des réseaux de cinquième génération (5G) et des réseaux véhiculaire (V2X) a ouvert une ère de connectivité et de services associés sans précédent. Ces réseaux permettent des interactions fluides entre les véhicules, l'infrastructure, et bien plus encore, en fournissant une gamme de services à travers des tranches de réseau (slices), chacune adaptée aux besoins spécifiques de ceux-ci. Les générations futures sont même censées apporter de nouvelles avancées à ces réseaux. Cependant, ce progrès remarquable les expose à une multitude de menaces en matière de cybersécurité, dont bon nombre sont difficiles à détecter et à atténuer efficacement avec les contre mesures actuelles. Cela souligne la nécessité de mettre en oeuvre de nouveaux mécanismes avancés de détection d'intrusion pour garantir l'intégrité, la confidentialité et la disponibilité des données et des services.Un domaine suscitant un intérêt croissant à la fois dans le monde universitaire qu'industriel est l'Intelligence Artificielle (IA), en particulier son application pour faire face aux menaces en cybersécurité. Notamment, les réseaux neuronaux (RN) ont montré des promesses dans ce contexte, même si les solutions basées sur l'IA sont accompagnées de défis majeurs.Ces défis peuvent être résumés comme des préoccupations concernant l'efficacité et l'efficience. Le premier concerne le besoin des Systèmes de Détection d'Intrusions (SDI) de détecter avec précision les menaces, tandis que le second implique d'atteindre l'efficacité en termes de temps et la détection précoce des menaces.Cette thèse représente l'aboutissement de nos recherches sur l'investigation des défis susmentionnés des SDI basés sur l'IA pour les systemes 5G en général et en particulier 5G-V2X. Nous avons entamé notre recherche en réalisant une revue de la littérature existante. Tout au long de cette thèse, nous explorons l'utilisation des systèmes d'inférence floue (SIF) et des RN, en mettant particulièrement l'accent sur cette derniere technique. Nous avons utilisé des techniques de pointe en apprentissage, notamment l'apprentissage profond (AP), en intégrant des réseaux neuronaux récurrents et des mécanismes d'attention. Ces techniques sont utilisées de manière innovante pour réaliser des progrès significatifs dans la résolution des préoccupations liées à l'amélioration de l'efficacité et de l'efficience des SDI. De plus, nos recherches explorent des défis supplémentaires liés à la confidentialité des données lors de l'utilisation des SDIs basés sur l'AP. Nous y parvenons en exploitant les algorithmes d'apprentissage fédéré (AF) les plus récents
The emergence of Fifth Generation (5G) and Vehicle-to-Everything (V2X) networks has ushered in an era of unparalleled connectivity and associated services. These networks facilitate seamless interactions among vehicles, infrastructure, and more, providing a range of services through network slices, each tailored to specific requirements. Future generations are even expected to bring further advancements to these networks. However, this remarkable progress also exposes them to a myriad of security threats, many of which current measures struggle to detect and mitigate effectively. This underscores the need for advanced intrusion detection mechanisms to ensure the integrity, confidentiality, and availability of data and services.One area of increasing interest in both academia and industry spheres is Artificial Intelligence (AI), particularly its application in addressing cybersecurity threats. Notably, neural networks (NNs) have demonstrated promise in this context, although AI-based solutions do come with inherent challenges. These challenges can be summarized as concerns about effectiveness and efficiency. The former pertains to the need for Intrusion Detection Systems (IDSs) to accurately detect threats, while the latter involves achieving time efficiency and early threat detection.This dissertation represents the culmination of our research findings on investigating the aforementioned challenges of AI-based IDSs in 5G systems in general and 5G-V2X in particular. We initiated our investigation by conducting a comprehensive review of the existing literature. Throughout this thesis, we explore the utilization of Fuzzy Inference Systems (FISs) and NNs, with a specific emphasis on the latter. We leveraged state-of-the-art NN learning, referred to as Deep Learning (DL), including the incorporation of recurrent neural networks and attention mechanisms. These techniques are innovatively harnessed to making significant progress in addressing the concerns of enhancing the effectiveness and efficiency of IDSs. Moreover, our research delves into additional challenges related to data privacy when employing DL-based IDSs. We achieve this by leveraging and experimenting state-of-the-art federated learning (FL) algorithms

Cette thèse présente un cadre flexible basé sur l'apprentissage par renforcement des files d'attente pour l'orchestration dynamique des tranches dans les réseaux Beyond 5G, prenant en charge de multiples tranches concurrentes qui couvrent différents domaines technologiques et sont régies par divers accords de niveau de service de bout en bout. Différentes méthodes d'apprentissage par renforcement profond (mono ou multi-agents) sont étudiées pour résoudre les problèmes de complexité d'état et d'action liés à ces problèmes combinatoires, qui rendent l'utilisation d'algorithmes d'apprentissage par renforcement classique impraticable. La performance des schémas proposés est validée par des simulations dans des scénarios de trafic markovien synthétique et de trafic réel
This Thesis introduces a flexible Reinforcement Learning queuing-based framework for dynamic slice orchestration in Beyond 5G networks, supporting multiple concurrent slices that span different technological domains and are governed by diverse end-to-end Service Level Agreements. Different (Deep) Reinforcement Learning methods (single or multi-agent) are investigated to address the state and action complexity hurdles arising in such combinatorial problems, which render the use of "vanilla" Reinforcement Learning algorithms impractical. The performance of the proposed schemes is validated through simulations under both synthetic Markovian traffic and real traffic scenarios

[EN] Mobile communication systems are currently being developed with the aim of providing peak data rates up to 20 times higher to those of LTE-Advanced Rel 10. However, this performance improvement is often far from being the experimented performance by those users who are far from the Base Station (BS). In this sense, there exists a consensus on the fact that the best way to achieve the same quality for all users is with the use of heterogeneous networks composed of macrocells, microcells, femtocells, and relays. This dissertation addresses the use of Mobile Relays (MRs) to provide service to users who are at the cell-edge. MR is a natural extension of the fi xed relay in which users who are in the idle state could retransmit signals received from other transmitters to enhance data rates. This dissertation focuses on proposing and evaluating new techniques that manage the use of the MR in the new generation cellular networks. In particular, the dissertation studies MR from two complementary points of view. The first point of view investigates the MR management at the network level through a signaling protocol known as Media Independent Handover. The central idea of this mechanism is to use this signaling to connect the BS and the user in one of the following two manners. In the former, both entities are connected directly through the xG (x= 2, 3, 4, 5) wireless network. In the latter, there exists an xG connection between the BS and the MR and another one between the MR and the user through an IEEE 802.11 local wireless network. The investigations in this Thesis aim at fi nding a trade-of f between using multiple MRs and reducing signaling overhead. The second point of view deals with MR integration at air interface level. It consists in detecting, proposing, and evaluating new transmission techniques that solve the drawbacks derived from coherent detection. As with point-to-point systems, employing multiple antennas in a cooperative system can signi cantly improve the spectral efficiency of the systems with only one transmit antenna assuming that the channel estate information is available at the receiver. However, performing a coherent detection in a network assisted by relays consumes much more resources than a point-to-point network since the coherent detection requires the channel estimation of source-relay, relay-destination, and source-destination links. In this Thesis, the proposed solution is to use transmission techniques that do not need the channel knowledge to perform the detection. This dissertation evaluates the use of Single-User (SU) open-loop communication methods over temporally-correlated Rayleigh fading MIMO channels. On the other hand, in multi-carrier systems, the Thesis proposes to transmit the Grassmannian signaling (GS) in the virtual block formed by the coherence time and the coherence bandwidth. This proposal is due to the fact that GS achieves data rates approaching capacity over block-fading channels. However, this channel type is not common in real systems since channel correlation is often found in frequency, time, and space. For this reason, the next objective is to evaluate the performance of GS compared to the diversity transmission modes of LTE, analyzing the impact of user mobility and antenna correlation. Thanks to these investigations, we point that non-coherent systems are promising techniques in mobility scenarios with a high number of transmit antennas. This result motivates its relevance in the design of new SU open-loop transmission methods with multiple antennas. In downlink multi-user non-coherent scenarios, superposition coding and a suboptimum detection scheme are proposed. This detection system reduces the complexity respect to the maximum likelihood detection. Finally, this dissertation proposes that GS is transmitted in a new carrier type, where any reference signal is transmitted. In this way, the user would change its detection method to non-coherent.
[ES] Los sistemas de comunicaciones móviles están siendo desarrollados en la actualidad con el objetivo de ofrecer tasas de datos de pico hasta 20 veces mayores que las proporcionadas por LTE-Advanced Rel 10. Sin embargo, esta mejora en prestaciones está lejos de ser la experimentada por los usuarios que están lejos de la Estación Base (EB). En este sentido, existe un consenso en que la mejor manera de lograr la misma calidad para todos los usuarios es con el uso de redes heterogéneas formadas de macroceldas, microceldas, femtoceldas y relays. Esta Tesis estudia el uso del Relay Móvil (RM) para proporcionar servicio a usuarios que estén en el borde de la celda. El RM es una extensión natural del relay fijo en el cual los usuarios que están en reposo podrían retransmitir señales recibidas de otros transmisores para mejorar las tasas de datos. Esta Tesis se enfoca en proponer y evaluar nuevas técnicas que gestionen el uso del RM en las redes celulares de nueva generación. En particular, la Tesis estudia el MR desde dos puntos de vista complementarios. El primer punto de vista investiga la gestión del RM a nivel de red a través de un protocolo de señalización conocido como Media Independent Handover. La idea principal de este mecanismo es usar esta señalización para conectar la EB y el usuario en una de las siguientes dos maneras. En la primera, ambas entidades están conectadas directamente a través de la red inalámbrica xG (x=2, 3, 4, 5). En la segunda, existe una conexión xG entre la EB y el RM, y otra entre el RM y el usuario a través de una red inalámbrica local IEEE 802.11. Las investigaciones en esta Tesis buscan un compromiso entre usar múltiples RMs y reducir la carga de señalización. El segundo punto de vista trata de la integración del RM a nivel radio. Esto consiste en detectar, proponer y evaluar nuevas técnicas de transmisión que solucionen los inconvenientes derivados de la detección coherente. Como en los sistemas punto a punto, emplear múltiples antenas en un sistema cooperativo puede mejorar la efficiencia espectral respecto a los sistemas con una única antena transmisora asumiendo que el estado del canal está disponible en el receptor. Sin embargo, realizar una detección coherente en una red asistida con relays consume más recursos que una red punto a punto ya que la detección coherente requiere la estimación de canal de los enlaces fuente-relay, relay-destino y fuente-destino. La solución propuesta es usar técnicas de transmisión que no necesiten el conocimiento del canal para realizar la detección. Esta Tesis evalúa el uso de métodos de comunicación en lazo abierto a un único usuario sobre canales MIMO con desvanecimientos Rayleigh temporalmente correlados. Por otra parte, en sistemas multiportadora, se propone transmitir la Señalización Grassmannian (SG) en el bloque virtual formado por el tiempo de coherencia y el ancho de banda de coherencia. Esta propuesta se debe al hecho de que la SG alcanza tasas de datos cercanas a la capacidad en canales block-fading. Sin embargo, este tipo de canal no es común en sistemas reales puesto que la correlación del canal se encuentra a menudo en frecuencia, tiempo y espacio. Por esta razón, el siguiente objetivo es evaluar las prestaciones de la SG comparadas con los modos de transmisión de diversidad de LTE, analizando el impacto de la movilidad del usuario y la correlación de las antenas. Gracias a estas investigaciones, apuntamos que los sistemas no coherentes son técnicas prometedoras en escenarios con movilidad y un alto número de antenas transmisoras. En escenarios no coherentes multiusuario del enlace descendente, se propone utilizar superposition coding y un esquema de detección subóptimo que reduce la complejidad respecto a la detección de máxima verosimilitud. Finalmente, se propone que la SG sea transmitida en una nueva portadora donde ninguna señal de referencia se transmita. De esta forma, el usuar
[CAT] Els sistemes de comunicacions mòbils estan sent desenrotllats en l'actualitat amb l'objectiu d'oferir taxes de dades de pic fins a 20 vegades majors que les proporcionades per LTE-Advanced Rel 10. No obstant això, esta millora en prestacions està lluny de ser l'experimentada pels usuaris que estan lluny de l'Estació Base (EB). En este sentit, hi ha un consens en què la millor manera d'aconseguir la mateixa qualitat per a tots els usuaris és amb l'ús de xarxes heterogènies formades de macrocel·les, microcel·les, femtoceldas i relays. Esta Tesi estudia l'ús del Relay Mòbil (RM) per a proporcionar servici a usuaris que estiguen en el bord de la cel·la. El RM és una extensió natural del relay fix en el qual els usuaris que estan en repòs podrien retransmetre senyals rebudes d'altres transmissors per a millorar les taxes de dades. Esta Tesi s'enfoca a proposar i avaluar noves tècniques que gestionen l'ús del RM en les xarxes cel·lulars de nova generació. En particular, la Tesi estudia el MR des de dos punts de vista complementaris. El primer punt de vista investiga la gestió del RM a nivell de xarxa a través d'un protocol de senyalització conegut com Media Independent Handover. La idea principal d'este mecanisme és usar esta senyalització per a connectar l'EB i l'usuari en una de les següents dos maneres. En la primera, ambdós entitats estan connectades directament a través de la xarxa sense fil xG (x=2, 3, 4, 5) . En la segona, hi ha una connexió xG entre l'EB i el RM, i una altra entre el RM i l'usuari a través d'una xarxa sense fil local IEEE 802.11. Les investigacions en esta Tesi busquen un compromís entre usar múltiples RMs i reduir la càrrega de senyalització. El segon punt de vista tracta de la integració del RM a nivell ràdio. Açò consistix a detectar, proposar i avaluar noves tècniques de transmissió que solucionen els inconvenients derivats de la detecció coherent. Com en els sistemes punt a punt, emprar múltiples antenes en un sistema cooperatiu pot millorar l'efficiencia espectral respecte als sistemes amb una única antena transmissora assumint que l'estat del canal està disponible en el receptor. No obstant això, realitzar una detecció coherent en una xarxa assistida amb relays consumix més recursos que una xarxa punt a punt ja que la detecció coherent requerix l'estimació de canal dels enllaços font-relay, relay-destí i font-destí. La solució proposada és usar tècniques de transmissió que no necessiten el coneixement del canal per a realitzar la detecció. Esta Tesi avalua l'ús de mètodes de comunicació en llaç obert a un únic usuari sobre canals MIMO amb esvaïments Rayleigh temporalment correlats. D'altra banda, en sistemes multiportadora, es proposa transmetre la Senyalització Grassmannian (SG) en el bloc virtual format pel temps de coherència i l'amplada de banda de coherència. Esta proposta es deu al fet de que la SG aconseguix taxes de dades pròximes a la capacitat en canals block-fading. No obstant això, este tipus de canal no és comú en sistemes reals ja que la correlació del canal es troba sovint en freqüència, temps i espai. Per esta raó, el següent objectiu és avaluar les prestacions de la SG comparades amb els modes de transmissió de diversitat de LTE, analitzant l'impacte de la mobilitat de l'usuari i la correlació de les antenes. Gràcies a estes investigacions, apuntem que els sistemes no coherents són tècniques prometedores en escenaris amb mobilitat i un alt nombre d'antenes transmissores. En escenaris no coherents multiusuari de l'enllaç descendent, es proposa utilitzar superposition coding i un esquema de detecció subòptim que reduïx la complexitat respecte a la detecció de màxima versemblança. Finalment, es proposa que la SG siga transmesa en una nova portadora on cap senyal de referència es transmeta. D'esta manera, l'usuari canviaria el seu mètode de detecció a no coherent.
Cabrejas Peñuelas, J. (2016). Distributed cooperative MIMO in beyond 2020 wireless networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/63245
TESIS

The exponential growth of wireless networks and the number of connected devices as well as the emergence of new multimedia-based services have resulted in growing demands for high data-rate communications, and a spectrum crisis. Hence, new approaches are required for better utilization of spectrum and to address the high data- rate requirements in future wireless communication systems. Non-orthogonal multiple access (NOMA) has been envisioned as a promising multiple access technique for 5G and beyond wireless networks due to its potential to achieve high spectral efficiency (SE) and energy efficiency (EE) as well as to provide massive connectivity in supporting the proliferation of Internet of Things. In NOMA, multiple users can share the same wireless resources by applying superposition coding (SC) and power domain multi- plexing at the transmitter and employing successive interference cancellation (SIC) technique at the receiver for multi-user detection. NOMA outperforms conventional orthogonal multiple access (OMA) by simultaneously sharing the available communication resources between all users via the power domain multiplexing which offers a significant performance gain in terms of SE. In this thesis, several resource allocation problems have been addressed in NOMA based communication systems, in order to improve network performance in terms of power consumption, fairness and EE. In particular, the NOMA scheme has been studied in multiple-input-single-output transmissions where transmit beamformers are designed to satisfy quality of service using convex optimization techniques. To incorporate the channel uncertainties in beamforming design, robust schemes are proposed based on the worst-case design and the outage probabilistic-based design. Finally, the EE is investigated for non-clustering and clustering NOMA schemes with imperfect channel state information. To eliminate the interference between different clusters, zero-forcing beamformers are employed at the base station. Theoretical analysis and algorithmic solutions are derived and the performance of all these schemes has been verified using simulation results.

This thesis examines how Software Defined Network (SDN) and Network Virtualization (NV) technologies can make 5G and beyond mobile networks more flexible, scalable and programmable to support the performance demands of the emerging heterogeneous applications. In this direction, concepts like mobile network slicing, multi-tenancy, and multi-connectivity have been investigated and their performance is analyzed. The SDN paradigm is used to enable flexible resource allocation to the end users, improve network resource utilization and avoid or rapidly solve the network congestion problems. The proposed network architectures are 3rd Generation Partnership Project (3GPP) standards compliant and integrate Open Network Foundation (ONF) SDN specifications to ensure seamless interoperability between different standards and backward/forward compatibility. Novel mechanisms and algorithms to efficiently manage the resources of evolving 5G Time-Division Duplex (TDD) networks in a flexible manner are introduced. These mechanisms enable formation of virtual cells on-demand which allows diverse resource utilization from multiple eNBs to the users. Within the scope of this thesis, SDN-based frameworks to enhance the QoE of end user applications considering Time Division-Long Term Evolution (TD-LTE) small cells have also been developed and network resource sharing scenarios with Frequency-Division Duplex (FDD)/TDD coexistence has been studied. In addition, this thesis also proposes and investigates a novel service-oriented network slicing concept for evolving 5G TDD networks which involve traffic prediction mechanisms and includes user mobility. An analytical model is also introduced that formulates the network slice resource allocation as a weighted optimization problem. The evaluations of the proposed solutions are performed using 3GPP standard compliant simulation settings. The proposed solutions have been compared with the state-of-the art schemes and the performance gains offered by the proposed solutions have been demonstrated. Performance is evaluated considering metrics such as throughput, delay, network resource utilization etc. The Mean Opinion Score (MOS) metric is used for evaluating the Quality of Experience (QoE) for end-user applications. With the help of SDN-based network management algorithms investigated in this work, it is shown how 5G+ networks can be managed efficiently, while at the same time provide enhanced flexibility and programmability to improve the performance of diverse applications and services delivered over the network to the end users.

L'omniprésence des dispositifs mobiles équipés d'une connectivité Internet et de systèmes de positionnement, nous pousse à les considérer comme une ressource précieuse à exploiter. Dans cette thèse, nous abordons l'utilisation des dispositifs mobiles sous un nouvel angle. Nous considérons l'extension de la capacité du MEC en utilisant les ressources disponibles des dispositifs mobiles au-delà de la bordure du réseau d'infrastructure. L'objectif est de tirer parti de leurs ressources inexploitées pour traiter les tâches de calculs au profit du MEC de manière distribuée. Pour pouvoir s'appuyer sur des nœuds mobiles, il est fondamental que le MEC soit capable de connaître son environnement d'exploitation. Dans la première partie de la thèse, nous explorons la disponibilité temporelle des ressources au-delà du bord. Nous avons choisi d'étudier la co-localisation des terminaux et d'analyser leurs persistances dans une cellule. Puis, nous nous intéressons à l'allocation des tâches. Nous mettons l'accent sur l'aspect spatio-temporel en quantifiant les ressources qu'une cellule peut fournir pour effectuer une tâche MEC. Nous estimons le potentiel de tâches de calcul effectuées par les terminaux en fonction du temps de présence cumulé dans une cellule donnée et d'un délai d'achèvement donné. Les résultats permettent de déterminer les possibilités de décharger des tâches de calcul sur des dispositifs mobiles. En outre, ils permettent de connaître les emplacements où il est judicieux de délester les tâches et la durée des tâches pouvant être délestées
The pervasiveness of mobile devices equipped with internet connectivity and positioning systems leads us to regard them as a valuable resource to leverage. In this thesis, we tackle the use of mobile devices from a new perspective. We consider the extension of the capacity of the MEC by using the available resources of mobile devices beyond the edge of the infrastructure network. The goal is to leverage their untapped resources to process computation on behalf of the MEC in a distributed way. It is fundamental for the MEC to be aware of its operating environment to rely on mobile nodes. In the first part of the thesis, we have focused on the temporal availability of beyond-the-edge resources. We chose to investigate the co-location of terminals and analyze their persistence in a cell. Then, we turn our attention to task allocation. We shift the focus on the spatio-temporal aspect by quantifying the resources that a cell can provide to perform a MEC task. We estimate the potential amount of computational tasks performed by nodes based on the cumulative presence time in a given cell and a given completion delay. Results provide insight into the possibilities of offloading computing tasks on mobile nodes. Furthermore, it allows knowing the locations where it is advisable to offload tasks and the time duration of tasks offloadable

Abstract Future cellular networks need to support the ever-increasing demand of bandwidth-intensive applications and interconnection of people, devices, and vehicles. Small cell network (SCN)-based communication together with proximity- and social-aware connectivity is conceived as a vital component of these networks to enhancing spectral efficiency, system capacity, and quality-of-experience (QoE). To cope with diverse application needs for the heterogeneous ecosystem, radio resource management (RRM) is one of the key research areas for the fifth-generation (5G) network. The key goals of this thesis are to develop novel, self-organizing, and low-complexity resource management algorithms for emerging device-to-device (D2D) and vehicle-to-vehicle (V2V) wireless systems while explicitly modeling and factoring network contextual information to satisfy the increasingly stringent requirements. Towards achieving this goal, this dissertation makes a number of key contributions. First, the thesis focuses on interference management techniques for D2D-enabled macro network and D2D-enabled SCNs in the downlink, while leveraging users’ social-ties, dynamic clustering, and user association mechanisms for network capacity maximization. A flexible social-aware user association technique is proposed to maximize network capacity. The second contribution focuses on ultra-reliable low-latency communication (URLLC) in vehicular networks in which interference management and resource allocation techniques are investigated, taking into account traffic and network dynamics. A joint power control and resource allocation mechanism is proposed to minimize the total transmission power while satisfying URLLC constraints. To overcome these challenges, novel algorithms are developed by combining several methodologies from graph theory, matching theory and Lyapunov optimization. Extensive simulations validate the performance of the proposed approaches, outperforming state-of-the-art solutions. Notably, the results yield significant performance gains in terms of capacity, delay reductions, and improved reliability as compared with conventional approaches
Tiivistelmä Tulevaisuuden solukkoverkkojen pitää pystyä tukemaan yhä suurempaa kaistanleveyttä vaativia sovelluksia sekä yhteyksiä ihmisten, laitteiden ja ajoneuvojen välillä. Piensoluverkkoihin (SCN) pohjautuvaa tietoliikennettä yhdistettynä paikka- ja sosiaalisen tietoisuuden huomioiviin verkkoratkaisuihin pidetään yhtenä elintärkeänä osana tulevaisuuden solukkoverkkoja, joilla pyritään tehostamaan spektrinkäytön tehokkuutta, järjestelmän kapasiteettia sekä kokemuksen laatua (QoE). Radioresurssien hallinta (RRM) on eräs keskeisistä viidennen sukupolven (5G) verkkoihin liittyvistä tutkimusalueista, joilla pyritään hallitsemaan heterogeenisen ekosysteemin vaihtelevia sovellustarpeita. Tämän väitöstyön keskeisinä tavoitteina on kehittää uudenlaisia itseorganisoituvia ja vähäisen kompleksisuuden resurssienhallinta-algoritmeja laitteesta-laitteeseen (D2D) ja ajoneuvosta-ajoneuvoon (V2V) toimiville uusille langattomille järjestelmille, sekä samalla mallintaa ja tuottaa verkon kontekstikohtaista tietoa vastaamaan koko ajan tiukentuviin vaatimuksiin. Tämä väitöskirja edistää näiden tavoitteiden saavuttamista usealla keskeisellä tuloksella. Aluksi väitöstyössä keskitytään häiriönhallinnan tekniikoihin D2D:tä tukevissa makroverkoissa ja laskevan siirtotien piensoluverkoissa. Käyttäjän sosiaalisia yhteyksiä, dynaamisia ryhmiä sekä osallistamismekanismeja hyödynnetään verkon kapasiteetin maksimointiin. Verkon kapasiteettia voidaan kasvattaa käyttämällä joustavaa sosiaaliseen tietoisuuteen perustuvaa osallistamista. Toinen merkittävä tulos keskittyy huippuluotettavaan lyhyen viiveen kommunikaatioon (URLLC) ajoneuvojen verkoissa, joissa tehtävää resurssien allokointia ja häiriönhallintaa tutkitaan liikenteen ja verkon dynamiikka huomioiden. Yhteistä tehonsäädön ja resurssien allokoinnin mekanismia ehdotetaan kokonaislähetystehon minimoimiseksi samalla, kun URLLC rajoitteita noudatetaan. Jotta esitettyihin haasteisiin voidaan vastata, väitöstyössä on kehitetty uudenlaisia algoritmeja yhdistämällä graafi- ja sovitusteorioiden sekä Lyapunovin optimoinnin menetelmiä. Laajat tietokonesimuloinnit vahvistavat ehdotettujen lähestymistapojen suorituskyvyn, joka on parempi kuin uusimmilla nykyisillä ratkaisuilla. Tulokset tuovat merkittäviä suorituskyvyn parannuksia erityisesti kapasiteetin lisäämisen, viiveiden vähentämisen ja parantuneen luotettavuuden suhteen verrattuna perinteisiin lähestymistapoihin

La cinquième génération de réseaux cellulaires (5G) a été une véritable révolution des technologies du réseau d'accès radio et du réseau mobile de base, se présentant comme la génération de rupture qui permet la cohabitation d'applications et usages extrêmement diversifiés, unifiés au sein d'une même technologie. Néanmoins, la 5G n'est qu'un début : de nouveaux scénarios et défis émergent. Par conséquent, la communauté des chercheurs prépare le terrain pour les systèmes cellulaires au-delà de la 5G (B5G). À cet égard, plusieurs technologies habilitantes sont étudiées. Outre la radio intelligente, l'utilisation des mmWaves, la technologie MIMO massive, ou encore l'utilisation de full-duplex (FD). L'accès multiple non orthogonal (NOMA) est apparu comme une technologie prometteuse qui permet à plusieurs utilisateurs de partager les mêmes ressources et optimise ainsi l'allocation des ressources, réduit la latence, et améliore à la fois l'efficacité spectrale et énergétique. Ces avantages font de NOMA un candidat sérieux en tant que système d'accès multiple pour les futurs réseaux B5G, en particulier pour les applications de la eSanté. NOMA peut être combiné de manière flexible avec n'importe quelle technologie sans fil telle que la communication coopérative, le full-duplex (FD), mmWave et les modulations multi-porteuses (MCM).Cette thèse propose une étude approfondie de cette technologie émergente, en particulier le NOMA coopératif (CNOMA) qui est considéré comme une technologie prometteuse pour les systèmes sans fil B5G et des futurs réseaux de eSanté, en commençant par présenter ses principes de base ainsi que sa combinaison avec la technologie FD, la transmission MCM, l'apprentissage en profondeur, ainsi qu'à l'amélioration de la sécurité de la couche physique (PLS).Tout d'abord, cette thèse étudie les performances du taux d'erreur des systèmes FD-CNOMA avec les canaux d'évanouissement sans fil. De nouvelles expressions des taux d'erreur binaire sont dérivées. De plus, des analyses à SNR élevé sont effectuées, ce qui a montré que FD-CNOMA a un plancher d'erreur en raison des imperfections du SIC et des résidus des auto-interférences. Sur la base des expressions dérivées, un nouveau schéma de relais sélectif est proposé pour améliorer de manière opportuniste les performances du système, en utilisant la surcharge minimale d'informations d'état de canal (CSI).Deuxièmement, le CNOMA basé sur MCM est examiné sous des canaux doublement sélectifs. Dans le contexte de la eSanté, cela peut être projeté sur les cas d'utilisation d'urgence en ambulance. Plus important encore, cette thèse présente une méthode d'amélioration des performances pour les utilisateurs lointains des systèmes MCM-NOMA avec un SIC imparfait et CSI imparfait sous des canaux sans fil doublement sélectifs. Deux schémas efficaces d'annulation d'interférence sont proposés pour améliorer le CNOMA basé sur MCM. Les schémas proposés sont robustes pour des scénarios de mobilité élevée avec une complexité de calcul relativement faible.Troisièmement et enfin, les progrès de l'apprentissage profond basé sur les réseaux de neurones (DNN) ont attiré une grande attention dans la communauté des communications sans fil (WCS). L'apprentissage profond a trouvé un large éventail d'applications dans les systèmes sans fil. Cependant, les DNN sont connus pour être très sensibles aux attaques contradictoires. De nombreuses attaques contradictoires robustes visant des systèmes sans fil basés sur les DNN ont été proposées dans la littérature. Cela devient un défi majeur pour la sécurité de la couche physique (PLS). Pour surmonter cette vulnérabilité, cette thèse propose une nouvelle technique de défense dont l'objectif est de protéger la victime sans dégrader la précision de son modèle de base en l'absence d'attaque. Les résultats obtenus sont très prometteurs et confirment que la technique de défense proposée peut améliorer la PLS d'une manière significative
The fifth generation of cellular networks (5G) was a real revolution in radio access technologies and mobile networks, presenting itself as the breakthrough generation that allowed the coexistence of extremely diversified applications and usage scenarios, unified under the same standard. Nevertheless, 5G is just the beginning: new scenarios and challenges are emerging. Therefore, the research community is pushing the research ahead and preparing the ground for beyond 5G (B5G) cellular systems. In this regard, several enabling technologies are investigated. In addition to the cognitive radio (CR), mmWave, massive MIMO, or even the use of full-duplex (FD), non-orthogonal multiple access (NOMA) emerged as a promising technology that allows multiple users to share the same resource block and hence, optimizes resource allocation, reduces the end-to-end latency, and improves both spectrum and energy efficiencies. Those advantages make NOMA a serious candidate as a multiple access scheme for future B5G networks, especially for the demanding eHealth applications. Furthermore, NOMA can be flexibly combined with any wireless technology such as cooperative communication, FD, mmWave, and multicarrier modulation (MCM).Motivated by this treatise, this thesis provides a comprehensive and intensive examination of this emerging technology, particularly, cooperative NOMA (CNOMA) which is considered a promising enabling technology for future B5G eHealth networks, from the basic principles to its combination with the full-duplex technology, MCM transmission, to deep learning as well as enhancing the physical layer security (PLS).First, this thesis investigates the error rate performance of FD-CNOMA systems over wireless fading channels. New closed-form expressions of the exact bit error rates (BER) are derived. Moreover, high-SNR analyses are conducted, which reveals that FD-CNOMA has an error floor due to the successive interference cancellation (SIC) imperfections and residual self-interference (RSI). Based on the derived expressions, a novel selective relaying scheme is proposed to opportunistically improve the system performance using the minimal channel state information (CSI) overhead.Second, the MCM-based CNOMA is examined under doubly selective channels encountered in vehicular and railway wireless communications. In the eHealth context, this can be projected to ambulance emergency healthcare use cases. More importantly, this thesis presents a performance improvement method for cell-edge users of MCM-NOMA systems with imperfect SIC and imperfect CSI under doubly selective wireless channels. Two efficient iterative interference cancellation schemes are proposed to enable user relaying for MCM-based CNOMA. The proposed schemes are robust for high mobility scenarios with a relatively low computational complexity.Third and last, advances in machine learning based on deep neural networks (DNNs) attracted great attention in the wireless communication community (WCS). It is regarded as a key component of B5G networks. Deep learning has found a broad range of applications in wireless systems, e.g., spectrum sensing, waveform design, SIC, and channel estimation. However, DNNs are known to be highly susceptible to adversarial attacks. Many robust over-the-air adversarial attacks against DNN-based WCS have been proposed in the literature. This is becoming a major challenge facing the physical layer security (PLS) of DNN-based WCS. To overcome this vulnerability, this thesis proposes a novel robust defense approach. The objective of our defense is to protect the victim without significantly degrading the accuracy of its baseline model in the absence of the attack. The obtained results are very promising and confirm that the proposed defense technique can enhance significantly the PLS of future DNN-based WCS

Les réseaux sans fil de la cinquième génération (5G) et au-delà (B5G), devraient être très hétérogènes, multicouches, et dotés d’une intelligence intégrée à la fois au cœur et à la périphérie du réseau. Dans un tel contexte, l’évaluation des performances au niveau du système revêtira une importance cruciale pour formuler des enseignements judicieux sur les compromis qui régissent un tel système complexe et ainsi prévenir le besoin de simulations logicielles coûteuses et fastidieuses. Au cours de la dernière décennie, la géométrie stochastique est considérée comme un puissant outil d’analyse permettant d’évaluer les performances des réseaux sans fil au niveau du système et de cerner leur tendance à l’hétérogénéité. Cette thèse examine les nouveaux modèles et techniques de la géométrie stochastique développés au cours de la précédente décennie en matière de modélisation et d’analyse des réseaux sans fil du futur. Les discussions sont suffisamment affinées pour être accessibles aux lecteurs peu spécialisés et faire en sorte que les lecteurs débutants, intermédiaires ou avancés puissent se familiariser rapidement avec ce domaine de recherche. Ensuite, nous nous appuyons sur la géométrie stochastique pour examiner plusieurs aspects des réseaux sans fil 5G et B5G, afin d’illustrer sa flexibilité mathématique et sa capacité à saisir l’analyse de scénarii peu conventionnels. Nous discutons également de nouvelles perspectives qui apporteront un nouveau souffle à l’utilisation de la géométrie stochastique au cours de cette décennie cruciale. En bref, les discussions furent étendues à des thématiques plus larges telles que les communications optiques en espace libre (FSO), les communications en lumière visible, les systèmes de drones, l’architecture d’accès radio en brouillard (F-RAN), l’intelligence artificielle et l’apprentissage machine, ainsi que les communications moléculaires
Next generation wireless networks, i.e., fifth generation (5G) and beyond (B5G), are expected to be highly heterogeneous, multilayered, with embedded intelligence at both thecore and edge of the network. In such a context, system-level performance evaluation will be very important to formulate relevant insights into tradeoffs that govern such a complex system and then prevent the need for onerous and timeconsuming computer simulations. Over the past decade, stochastic geometry has emerged as a powerful analytical tool to evaluate system-level performance of wireless networks and capture their tendency towards heterogeneity. This dissertation reviews first novel stochastic geometry models and techniques developed during the last decade in modeling and analysis of modern wireless networks. The discussions are refined enough to be accessible for non-specialist readers and help new, intermediate, or advanced readers familiarize quickly with this field of research. Next, we leverage stochastic geometry frameworks to investigate several aspects of 5G and B5G wireless networks and then illustrate its mathematical flexibility and ability to capture the analysis of the rather unconventional scenarios. Also, new perspectives that will breathe new life into the use of stochastic geometry during this crucial decade are discussed. In a nutshell, extensive discussions were held on broader topics such as free space (FSO) optical communications, visible light communications, unmanned aerial vehicle systems, fog radio access architecture (F-RAN) , artificial intelligence and machine learning, and molecular communications

Abstract The aim of this thesis is to devise new paradigms on radio resource sharing including cache-enabled virtualized large cellular networks for mobile network operators (MNOs). Also, self-organizing resource allocation for small cell networks is considered. In such networks, the MNOs rent radio resources from the infrastructure provider (InP) to support their subscribers. In order to reduce the operational costs, while at the same time to significantly increase the usage of the existing network resources, it leads to a paradigm where the MNOs share their infrastructure, i.e., base stations (BSs), antennas, spectrum and edge cache among themselves. In this regard, we integrate the theoretical insights provided by stochastic geometrical approaches to model the spectrum and infrastructure sharing for large cellular networks. In the first part of the thesis, we study the non-orthogonal multi-MNO spectrum allocation problem for small cell networks with the goal of maximizing the overall network throughput, defined as the expected weighted sum rate of the MNOs. Each MNO is assumed to serve multiple small cell BSs (SBSs). We adopt the many-to-one stable matching game framework to tackle this problem. We also investigate the role of power allocation schemes for SBSs using Q-learning. In the second part, we model and analyze the infrastructure sharing system considering a single buyer MNO and multiple seller MNOs. The MNOs are assumed to operate over their own licensed spectrum bands while sharing BSs. We assume that multiple seller MNOs compete with each other to sell their infrastructure to a potential buyer MNO. The optimal strategy for the seller MNOs in terms of the fraction of infrastructure to be shared and the price of the infrastructure, is obtained by computing the equilibrium of a Cournot-Nash oligopoly game. Finally, we develop a game-theoretic framework to model and analyze a cache-enabled virtualized cellular networks where the network infrastructure, e.g., BSs and cache storage, owned by an InP, is rented and shared among multiple MNOs. We formulate a Stackelberg game model with the InP as the leader and the MNOs as the followers. The InP tries to maximize its profit by optimizing its infrastructure rental fee. The MNO aims to minimize the cost of infrastructure by minimizing the cache intensity under probabilistic delay constraint of the user (UE). Since the MNOs share their rented infrastructure, we apply a cooperative game concept, namely, the Shapley value, to divide the cost among the MNOs
Tiivistelmä Tämän väitöskirjan tavoitteena on tuottaa uusia paradigmoja radioresurssien jakoon, mukaan lukien virtualisoidut välimuisti-kykenevät suuret matkapuhelinverkot matkapuhelinoperaattoreille. Näiden kaltaisissa verkoissa operaattorit vuokraavat radioresursseja infrastruktuuritoimittajalta (InP, infrastructure provider) asiakkaiden tarpeisiin. Toimintakulujen karsiminen ja samanaikainen olemassa olevien verkkoresurssien hyötykäytön huomattava kasvattaminen johtaa paradigmaan, jossa operaattorit jakavat infrastruktuurinsa keskenään. Tämän vuoksi työssä tutkitaan teoreettisia stokastiseen geometriaan perustuvia malleja spektrin ja infrastruktuurin jakamiseksi suurissa soluverkoissa. Työn ensimmäisessä osassa tutkitaan ei-ortogonaalista monioperaattori-allokaatioongelmaa pienissä soluverkoissa tavoitteena maksimoida verkon yleistä läpisyöttöä, joka määritellään operaattoreiden painotettuna summaläpisyötön odotusarvona. Jokaisen operaattorin oletetaan palvelevan useampaa piensolutukiasemaa (SBS, small cell base station). Työssä käytetään monelta yhdelle -vakaata sovituspeli-viitekehystä SBS:lle käyttäen Q-oppimista. Työn toisessa osassa mallinnetaan ja analysoidaan infrastruktuurin jakamista yhden ostaja-operaattorin ja monen myyjä-operaattorin tapauksessa. Operaattorien oletetaan toimivan omilla lisensoiduilla taajuuksillaan jakaen tukiasemat keskenään. Myyjän optimaalinen strategia infrastruktuurin myytävän osan suuruuden ja hinnan suhteen saavutetaan laskemalla Cournot-Nash -olipologipelin tasapainotila. Lopuksi, työssä kehitetään peli-teoreettinen viitekehys virtualisoitujen välimuistikykenevien soluverkkojen mallintamiseen ja analysointiin, missä InP:n omistama verkkoinfrastruktuuri vuokrataan ja jaetaan monen operaattorin kesken. Työssä muodostetaan Stackelberg-pelimalli, jossa InP toimii johtajana ja operaattorit seuraajina. InP pyrkii maksimoimaan voittonsa optimoimalla infrastruktuurin vuokrahintaa. Operaattori pyrkii minimoimaan infrastruktuurin hinnan minimoimalla välimuistin tiheyttä satunnaisen käyttäjän viive-ehtojen mukaisesti. Koska operaattorit jakavat vuokratun infrastruktuurin, työssä käytetään yhteistyöpeli-ajatusta, nimellisesti, Shapleyn arvoa, jakamaan kustannuksia operaatoreiden kesken

La virtualisation des fonctions réseau (NFV) est le pilier fondateur de l'architecture 5G basée sur les services. La NFV a débuté en 2012, avec les fonctions de réseau virtuelles (VNF) basées sur les machines virtuelles (VM). Les conteneurs sont devenus une technologie alternative de conditionnement intéressante pour la virtualisation des fonctions réseau. Le conteneur est léger en termes de consommation de ressources ce qui améliore son temps d'instanciation. Outre les fonctions de réseau, la conteneurisation peut être un outil prometteur pour les applications multi-access edge computing (MEC) qui abritent des services exigeants à faible latence. La rareté des ressources à la périphérie du réseau exige des technologies qui utilisent efficacement les ressources de calcul, de stockage et de mise en réseau. La conteneurisation est censée être utilisée dans le cadre des principes fondamentaux de la conception d'applications cloud-native, une architecture basée sur des microservices à couplage lâche, d'une évolutivité à la demande et d'une résilience élevée. La flexibilité et l'agilité des conteneurs peuvent certainement profiter au découpage du réseau 5G en tranches,ces derniers reposent fortement sur NFV et MEC. Le concept de découpage du réseau permet de créer des réseaux logiques isolés au-dessus du même réseau physique. Une tranche de réseau peut avoir des fonctions de réseau dédiées, partagées entre plusieurs tranches. En effet, l'orchestration des tranches de réseau nécessite une interaction avec de multiples orchestrateurs de domaines technologiques: l'accès radio, le transport, le réseau central et l'informatique périphérique. Le changement de paradigme consistant à utiliser des principes de conception d'applications cloud-natives a créé des défis pour les systèmes d'orchestration existants et les normes NFV et MEC de l'ETSI. Ces derniers ont été conçus pour gérer des fonctions de réseau basées sur des machines virtuelles. Ils sont donc limités dans leur approche de la gestion d'une fonction de réseau cloud-native. Par le présent manuscrit, nous examinons les normes existantes de l'ETSI NFV, de l'ETSI MEC et des orchestrateurs de services/tranches de réseau, nous proposons de résoudre les défis liés à l'orchestration de tranches de réseau multi-domaines cloud-native. Pour cela, nous proposons tout d'abord un service d'information sur le réseau radio (RNIS) MEC qui a la capacité de fournir des informations radio au niveau de l'abonné dans un environnement NFV. Deuxièmement, nous fournissons un algorithme d'allocation et de placement dynamique des ressources (DRAP) pour placer les services réseau cloud-natives en tenant compte de leur matrice de coût et de disponibilité. Troisièmement, en combinant NFV, MEC et Network Slicing, nous proposons un nouveau mécanisme d'orchestration de tranches MEC (LeSO) pour surmonter les défis liés à l'orchestration de tranches MEC. Quatrièmement, le mécanisme proposé offre un modèle de déploiement de tranches de réseau qui permet de multiples possibilités de conception d'applications MEC. Ces possibilités ont été étudiées plus en détails pour comprendre l'impact de l'architecture de conception microservice sur la disponibilité et la latence de l'application. Enfin, tous ces travaux sont combinés pour proposer une nouvelle approche d'orchestration de tranches légères Cloud-native (CLiSO) étendant le précédant mécanisme d'orchestration de tranches légères de bord (LeSO). Cette nouvelle approche offre un modèle de tranche de réseau agnostique sur le plan technologique et orienté déploiement. La solution a été évaluée de manière approfondie en orchestrant les fonctions réseau du conteneur OpenAirInterface sur des plateformes de cloud public et privé. Les résultats expérimentaux montrent que la solution proposée a des empreintes de ressources plus faibles que les orchestrateurs existants et prend moins de temps pour orchestrer les tranches de réseau
Network Function Virtualization (NFV) is the founding pillar of 5G Service Based Architecture. It has the potential to revolutionize the future mobile communication generations. NFV started long back in 2012 with Virtual-Machine (VM) based Virtual Network Functions (VNFs). The use of VMs raised multiple questions because of the compatibility issues between VM hypervisors and their high resource consumption. This made containers to be an alternative network function packaging technology. The lightweight design of containers improves their instantiation time and resource footprints. Apart from network functions, containerization can be a promising enabler for Multi-access Edge Computing (MEC) applications that provides a home to low-latency demanding services. Edge computing is one of the key technology of the last decade, enabling several emerging services beyond 5G (e.g., autonomous driving, robotic networks, Augmented Reality (AR)) requiring high availability and low latency communications. The resource scarcity at the edge of the network requires technologies that efficiently utilize computational, storage, and networking resources. Containers' low-resource footprints make them suitable for designing MEC applications. Containerization is meant to be used in the framework of cloud-native application design fundamentals, loosely coupled microservices-based architecture, on-demand scalability, and high resilience. The flexibility and agility of containers can certainly benefit 5G Network Slicing that highly relies on NFV and MEC. The concept of Network slicing allows the creation of isolated logical networks on top of the same physical network. A network slice can have dedicated network functions or its network functions can be shared among multiple slices. Indeed, network slice orchestration requires interaction with multiple technological domain orchestrators, access, transport, core network, and edge computing. The paradigm shift of using cloud-native application design principles has created challenges for legacy orchestration systems and the ETSI NFV and MEC standards. They were designed for handling virtual machine-based network functions, restricting them in their approach to managing a cloud-native network function. The thesis examines the existing standards of ETSI NFV, ETSI MEC, and network service/slice orchestrators. Aiming to overcome the challenges around multi-domain cloud-native network slice orchestration. To reach the goal, the thesis first proposes MEC Radio Network Information Service (RNIS) that can provide radio information at the subscriber level in an NFV environment. Second, it provides a Dynamic Resource Allocation and Placement (DRAP) algorithm to place cloud-native network services considering their cost and availability matrix. Third, by combining NFV, MEC, and Network Slicing, the thesis proposes a novel Lightweight edge Slice Orchestration framework to overcome the challenges around edge slice orchestration. Fourth, the proposed framework offers an edge slice deployment template that allows multiple possibilities for designing MEC applications. These possibilities were further studied to understand the impact of the microservice design architecture on application availability and latency. Finally, all this work is combined to propose a novel Cloud-native Lightweight Slice Orchestration (CLiSO) framework extending the previously proposed Lightweight edge Slice Orchestration (LeSO) framework. In addition, the framework offers a technology-agnostic and deployment-oriented network slice template. The framework has been thoroughly evaluated via orchestrating OpenAirInterface container network functions on public and private cloud platforms. The experimental results show that the framework has lower resource footprints than existing orchestrators and takes less time to orchestrate network slices

The aim of this interdisciplinary work, with roots in business economics and engineering, is to propose a new and innovative business model starting from a description of existing business models enabled by 5G and 6G. The new business model, called the sharing platform business model (SPBM), is based on the concept of sharing economy and multi-sided business model. The SPBM exploits the advantages of a platform, which facilitates the collaboration and cooperation among all the stakeholders in the 5G ecosystem. The ongoing fifth generation of mobile networks has disrupted, in a positive way, the future wireless communication networks; the most significant novelty compared to previous generations is the capability of 5G to serve the requirements of the vertical industries. 5G and the future 6G are able to transform industries and to provide services at gigabit/s speeds, low latency and to open new business opportunities. The mobile ecosystem has completely changed, previous generations were based on voice and data services and business models characterized by a bilateral relationship between operators and their customers, on the other hand, 5G offers the opportunity to collaborate with vertical industries to provide new services for enterprises. Given these premises, there is a clear need for a complete change in business modelling to overcome traditional models and to pave the way for innovative business models, which shall be able to face the business transformation of the mobile ecosystem. One of the main factors responsible for the change in business modelling is the uncertainty regarding the network investors: while in traditional business models the investors were mainly the MNOs, in the new mobile ecosystem this aspect is unclear. The question is: who should invest in the network infrastructure? Probably the solution could be the creation of public-private partnerships but building a business model based on this premise is completely a novel exercise.

L'architecture de découpage du réseau en sous-réseaux "Network slicing", rendue possible grâce aux nouvelles technologies telles que la virtualisation des fonctions réseau (NFV) et le réseau défini par logiciel (SDN), est l'un des principaux piliers des réseaux 5G et au-delà (B5G). Dans les environnements de la cinquième génération et au-delà (B5G), on s'attend à une multiplication du nombre de sous-réseaux coexistant, plus ou moins complexes, avec des durées de vie, des besoins en ressources et des objectifs de performance très divers. Cela crée des défis importants pour la gestion et l'orchestration des sous-réseaux sans intervention humaine, y compris la sécurité, la gestion des pannes et la confiance. En outre, le découpage du réseau ouvre le marché à de nouvelles parties prenantes, à savoir le vertical ou le locataire, le fournisseur de tranches de réseau et le fournisseur d'infrastructure. Dans ce contexte, il est nécessaire d'assurer non seulement une interaction sécurisée entre ces acteurs, mais aussi que chaque acteur fournisse le service attendu pour répondre aux exigences des sous-réseaux. Il convient donc de concevoir de nouvelles architectures sécurisées capables d'identifier/détecter en temps réel les nouvelles formes d'attaques liées au découpage de réseaux en tranches, tout en gérant de manière sûre et automatique les accords de niveau de service (SLAs) entre les acteurs impliqués. Dans cette thèse, nous concevons une nouvelle architecture sécurisée adaptée aux réseaux prêts pour le "Network slicing" (réseaux de cinquième génération (5G) et au-delà), en nous appuyant fortement sur la blockchain et l'intelligence artificielle (IA) pour permettre une gestion sécurisée et fiable des sous-réseaux
Network slicing architecture, enabled by new technologies such as Network Functions Virtualization (NFV) and Software-Defined Networking (SDN), is one of the main pillars of Fifth-generation and Beyond (B5G). In B5G settings, the number of coexisting slices with varying degrees of complexity and very diverse lifespans, resource requirements, and performance targets is expected to explode. This creates significant challenges towards zero-touch slice management and orchestration, including security, fault management, and trust. In addition, network slicing opens the business market to new stakeholders, namely the vertical or tenant, the network slice provider, and the infrastructure provider. In this context, there is a need to ensure not only a secure interaction between these actors, but also that each actor delivers the expected service to meet the network slice requirements. Therefore, new trust architectures should be designed, which are able to identify/detect the new forms of slicing-related attacks in real-time, while securely and automatically managing Service Level Agreements (SLA) among the involved actors. In this thesis, we devise new security architectures tailored to network slicing ready networks (B5G), heavily relying on blockchain and Artificial Intelligence (AI) to enable secure and trust network slicing management

Alors que l'architecture centralisée et autonome existante des opérateurs de réseaux mobiles (ORM) fournit une connectivité à des milliards d'utilisateurs, ils souffrent d'un manque de mécanismes techniques pour améliorer la collaboration entre les MNO et les autres fournisseurs.Cela a des impacts sur les coûts de mutualisation, ainsi que sur la consommation d'énergie et l'impact environnemental. Cela peut également empêcher l'avènement de modèles commerciaux plus collaboratifs avec d'autres fournisseurs ou même avec des clients. De plus, la complexité des réseaux au-delà de la 5G peut dépasser la capacité d'un ORM à gérer le coût et la complexité. Enfin, les architectures MNO existantes souffrent également de leur centralisation, problèmes techniques et vulnérabilités.Relever ces défis n'est pas un voyage simple. Cependant, nous croyons qu'il y a un intérêt à proposer à la communauté de la recherche en télécommunications une approche de table rase. De telles solutions alternatives doivent - au moins - avoir un écosystème distribué/décentralisé, assurer la fiabilité entre les acteurs dans l'environnement méfiant, partager les ressources entre les parties prenantes, apporter une automatisation plus élevée et fournir une sécurité et une confidentialité suffisantes.La blockchain est une technologie de registre distribué peer-to-peer qui ne peut être mise à jour que par consensus entre la majorité des nœuds participants sur le réseau. En raison de ses caractéristiques intrinsèques, la Blockchain et les smart contrats peuvent réduire le coût, la latence et la complexité de la collaboration entre les entités d'un réseau cellulaire multi-acteurs tout en augmentant la fiabilité, la traçabilité et les capacités de supervision.Ce travail propose un système de connectivité mobile multi-acteurs qui fournit une solution distribuée et sécurisée prou les entités et les acteurs de l'écosystème du réseau cellulaire. Pour ce faire, ce travail fournit dans un premier temps une étude complète des défis existants dans les réseaux cellulaires actuels concernant les aspects commerciaux et de collaboration, les problèmes techniques et la sécurité. Les résultats de ces études nous ont amenés à proposer deux contributions principales, l'une concernant la coopération entre les différents acteurs de l'écosystème des réseaux cellulaires, et l'autre pour la collaboration entre les ORM pour la gestion des identités et des profils.Plus précisément, la première contribution propose un nouvel écosystème de télécommunications hybride (distribué-décentralisé) pour façonner la conception des réseaux au-delà de la 5G et de la 6G. Cette méthode offre la possibilité d'éliminer toute autorité centrale, d'augmenter la tolérance aux pannes du système, de simplifier les procédures informatiques et de sécuriser le paiement entre les entités.La deuxième contribution introduit une nouvelle gestion des profils d'utilisateurs et un portage des numéros et des profils mobiles en plus de la Blockchain et des contrats intelligents. Cette méthode vise à éliminer l'autorité centrale dans la procédure de portage en créant un système plus collaboratif et distribué dans ce but, à augmenter l'automatisation et la confiance, et à remédier à la latence élevée de la méthode existante de portage des ORM. De plus, il offre la possibilité de porter les profils des utilisateurs vers l'ORM destinataire ainsi que le numéro de téléphone avec une procédure automatisée sans autorité centralisée ni tiers.Pour évaluer le système proposé et analyser sa faisabilité de mise en œuvre, nous avons proposé trois scénarios de déploiement dans lesquels la Blockchain peut être logiquement positionnée soit en RAN, cœur de réseau, ou couche de service. Les résultats de l'évaluation montrent que le système est suffisamment évolutif en ce qui concerne le nombre d'acteurs et de collaborateurs, et en fonction des exigences du réseau, ses performances et son niveau de sécurité sont ajustables
While the existing centralized and stand-alone architecture of Mobile Network Operators (MNO) provides connectivity to billions of users, they suffer from a lack of technical mechanisms to enhance collaboration between MNOs and other providers.This has impacts on mutualization costs, as well as on energy consumption and environmental impact. This may also prevent the advent of more collaborative business models with other providers or even with customers. Moreover, the complexity of 5G and beyond 5G networks may surpass the capability of one MNO to manage the cost and the complexity of connection. Finally, existing MNO architectures also suffer from their centralization, resulting in several technical issues and vulnerabilities.Addressing these challenges is not a straightforward journey. MNO architectures have been defined for nearly three decades by well-established standardization bodies. However, we believe there is an interest in proposing to the telecom research community a clean-slate approach. Such alternative solutions need to -at least- have a distributed/ decentralized ecosystem, provide trustworthiness between actors in the distrusted environment, share the resources among stakeholders, bring higher automation, and provide sufficient security and privacy. Any alternative addressing these requirements would be a promising potential solution.Blockchain is a peer-to-peer distributed ledger, cryptographically secure, append-only, immutable, traceable, and transparent technology that is only updateable via consensus among a majority of the participating nodes on the network. Due to its intrinsic features, Blockchain, and smart contracts can decrease the cost, latency, and complexity of collaboration among entities in multi-actor cellular network while increasing the trustworthiness, traceability, and supervision abilities.This work proposes a multi-actor mobile connectivity system that provides a distributed, trustful, automated, low-cost, and secure solution for the entities and actors of the cellular network ecosystem. To do so, this work provides at first a comprehensive study of the existing challenges in current cellular networks regarding business and collaboration aspects, technical issues, and security. The results of these studies have led us to propose two main contributions, one regarding the cooperation among different actors of the cellular network ecosystem (i.e., MNOs, service providers, small-scale businesses, vendors, and end-users) and another for collaboration among MNOs (and potentially with regulation bodies) for identity and profile management.More precisely, the first contribution proposes a novel hybrid (distributed-decentralized) telecommunication ecosystem to shape the beyond 5G and 6G network design. This method provides the opportunity to eliminate any central authority, increase the fault tolerance of the system, simplifies IT procedures, and provide secure payment among entities.The second contribution introduces a new user profile management and mobile number and profile porting on top of Blockchain and smart contracts. This method aims to eliminate the central authority in the porting procedure by creating a more collaborative and distributed system to this aim, increase automation and trustfulness, and address the high latency of the existing method for porting the MNOs. Moreover, it brings the opportunity of porting the users' profiles to the recipient MNO as well as the phone number with an automated procedure without a centralized authority or third parties.To evaluate the proposed system and analyze its implementation feasibility, we proposed three deployment scenarios in which the Blockchain can be logically positioned either in RAN, core network, or service layer. The evaluation results show that the system is scalable enough regarding the number of actors and collaborators, and based on the network requirements, its performance and security level are adjustable

Location awareness is a key enabler for a variety of verticals and use cases (UCs) in 5th generation (5G) and beyond 5G (B5G) networks, including those related to autonomy, logistic, smart environments, and Industry 4.0. However, fulfilling the key performance indicator (KPI) requirements for such UCs is challenging. This calls for new localiztion algorithms able to learn from the environment and to fully leverage the positional information provided by the network measurements. Moreover, the integration of next generation cellular networks with sensor radar networks (SRNs), will be fundamental to further enhance these new verticals, as well as to improve the communication performance and the network resource management. This calls for an accurate modeling of the wireless impairments and the design of algorithms able to provide physical analytics (e.g., number of person in a monitored area) in addition to location information. The main objectives of this thesis are: 1. design of machine learning based algorithms for localization in 5G and B5G networks; and 2. characterization of wireless impairments in SRNs, as well as the design of algorithms for extracting physical analytics via SRNs. In particular, this thesis presents the design of soft information (SI)-based localiza- tion algorithms exploiting both radio access technology (RAT)-dependent (obtained from the 5G network) and RAT-independent (obtained via non-3rd Generation Partnership Project (3GPP) technologies) measurements. Performance using both SI and classical approaches are quantified in 3GPP standardized scenarios via rigorous simulations in full conformity with 3GPP technical specifications and reports. Results show that the pro- posed SI approach significantly outperforms the approaches reported in 3GPP technical reports. In addition, a statistical characterization of the clutter for SRNs employing ultra-wideband (UWB) signals is provided based on experimental measurements carried out in an indoor environment. Lastly, a crowd-centric counting algorithm based on machine learning techniques is proposed and compared with state-of-the-art approaches based on experimental measurements.

En la actualidad, la Internet de las Cosas (Internet of Things, IoT) es una tecnología esencial para la próxima generación de sistemas inalámbricos. La conectividad es la base de IoT, y el tipo de acceso requerido dependerá de la naturaleza de la aplicación. Uno de los principales facilitadores del entorno IoT es la comunicación machine-to-machine (M2M) y, en particular, su enorme potencial para ofrecer conectividad ubicua entre dispositivos inteligentes. Las redes celulares son la elección natural para las aplicaciones emergentes de IoT y M2M. Un desafío importante en las redes celulares es conseguir que la red sea capaz de manejar escenarios de acceso masivo en los que numerosos dispositivos utilizan comunicaciones M2M. Por otro lado, los sistemas celulares han experimentado un tremendo desarrollo en las últimas décadas: incorporan tecnología sofisticada y nuevos algoritmos para ofrecer una amplia gama de servicios. El modelado y análisis del rendimiento de estas redes multiservicio es también una tarea desafiante que podría requerir un gran esfuerzo computacional. Para abordar los desafíos anteriores, nos centramos en primer lugar en el diseño y la evaluación de las prestaciones de nuevos mecanismos de control de acceso para hacer frente a las comunicaciones masivas M2M en redes celulares. Posteriormente nos ocupamos de la evaluación de prestaciones de redes multiservicio y proponemos una nueva técnica analítica que ofrece precisión y eficiencia computacional. Nuestro principal objetivo es proporcionar soluciones para aliviar la congestión en la red de acceso radio cuando un gran número de dispositivos M2M intentan conectarse a la red. Consideramos los siguientes tipos de escenarios: (i) los dispositivos M2M se conectan directamente a las estaciones base celulares, y (ii) forman grupos y los datos se envían a concentradores de tráfico (gateways) que les proporcionan acceso a la infraestructura. En el primer escenario, dado que el número de dispositivos añadidos a la red aumenta continuamente, esta debería ser capaz de manejar el considerable incremento en las solicitudes de acceso. El 3rd Generation Partnership Project (3GPP) ha propuesto el access class barring (ACB) como una solución práctica para el control de congestión en la red de acceso radio y la red troncal. El ajuste correcto de los parámetros de ACB de acuerdo con la intensidad del tráfico es crítico, pero cómo hacerlo de forma dinámica y autónoma es un problema complejo cuya solución no está recogida en las especificaciones del 3GPP. Esta tesis doctoral contribuye al análisis del rendimiento y al diseño de nuevos algoritmos que implementen efectivamente este mecanismo, y así superar los desafíos introducidos por las comunicaciones masivas M2M. En el segundo escenario, dado que la heterogeneidad de los dispositivos IoT y las arquitecturas celulares basadas en hardware imponen desafíos aún mayores para permitir una comunicación flexible y eficiente en los sistemas inalámbricos 5G, esta tesis doctoral también contribuye al diseño de software-defined gateways (SD-GWs) en una nueva arquitectura propuesta para redes inalámbricas definidas por software que se denomina SoftAir. Esto permite manejar tanto un gran número de dispositivos como el volumen de datos que estarán vertiendo en la red. Otra contribución de esta tesis doctoral es la propuesta de una técnica novedosa para el análisis de prestaciones de redes multiservicio de alta capacidad que se basa en un nuevo enfoque del modelizado analítico de sistemas que operan a diferentes escalas temporales. Este enfoque utiliza el análisis del transitorio de una serie de subcadenas absorbentes y lo denominamos absorbing Markov chain approximation (AMCA). Nuestros resultados muestran que para un coste computacional dado, AMCA calcula los parámetros de prestaciones habituales de un sistema con mayor precisión, en comparación con los resultados obtenidos por otr
Nowadays, Internet of Things (IoT) is an essential technology for the upcoming generation of wireless systems. Connectivity is the foundation for IoT, and the type of access required will depend on the nature of the application. One of the leading facilitators of the IoT environment is machine-to-machine (M2M) communication, and particularly, its tremendous potential to offer ubiquitous connectivity among intelligent devices. Cellular networks are the natural choice for emerging IoT and M2M applications. A major challenge in cellular networks is to make the network capable of handling massive access scenarios in which myriad devices deploy M2M communications. On the other hand, cellular systems have seen a tremendous development in recent decades; they incorporate sophisticated technology and algorithms to offer a broad range of services. The modeling and performance analysis of these large multi-service networks is also a challenging task that might require high computational effort. To address the above challenges, we first concentrate on the design and performance evaluation of novel access control schemes to deal with massive M2M communications. Then, we focus on the performance evaluation of large multi-service networks and propose a novel analytical technique that features accuracy and computational efficiency. Our main objective is to provide solutions to ease the congestion in the radio access or core network when massive M2M devices try to connect to the network. We consider the following two types of scenarios: (i) massive M2M devices connect directly to cellular base stations, and (ii) they form clusters and the data is forwarded to gateways that provide them with access to the infrastructure. In the first scenario, as the number of devices added to the network is constantly increasing, the network should handle the considerable increment in access requests. Access class barring (ACB) is proposed by the 3rd Generation Partnership Project (3GPP) as a practical congestion control solution in the radio access and core network. The proper tuning of the ACB parameters according to the traffic intensity is critical, but how to do so dynamically and autonomously is a challenging task that has not been specified. Thus, this dissertation contributes to the performance analysis and optimal design of novel algorithms to implement effectively this barring scheme and overcome the challenges introduced by massive M2M communications. In the second scenario, since the heterogeneity of IoT devices and the hardware-based cellular architectures impose even greater challenges to enable flexible and efficient communication in 5G wireless systems, this dissertation also contributes to the design of software-defined gateways (SD-GWs) in a new architecture proposed for wireless software-defined networks called SoftAir. The deployment of these SD-GWs represents an alternative solution aiming at handling both a vast number of devices and the volume of data they will be pouring into the network. Another contribution of this dissertation is to propose a novel technique for the performance analysis of large multi-service networks. The underlying complexity of the network, particularly concerning its size and the ample range of configuration options, makes the solution of the analytical models computationally costly. However, a typical characteristic of these networks is that they support multiple types of traffic flows operating at different time-scales. This time-scale separation can be exploited to reduce considerably the computational cost associated to determine the key performance indicators. Thus, we propose a novel analytical modeling approach based on the transient regime analysis, that we name absorbing Markov chain approximation (AMCA). For a given computational cost, AMCA finds common performance indicators with greater accuracy, when compared to the results obtained by other approximate methods proposed in the literature.
En l'actualitat, la Internet de les Coses (Internet of Things, IoT) és una tecnologia essencial per a la propera generació de sistemes sense fil. La connectivitat és la base d'IoT, i el tipus d'accés requerit dependrà de la naturalesa de l'aplicació. Un dels principals facilitadors de l'entorn IoT és la comunicació machine-to-machine (M2M) i, en particular, el seu enorme potencial per oferir connectivitat ubiqua entre dispositius intel · ligents. Les xarxes mòbils són l'elecció natural per a les aplicacions emergents de IoT i M2M. Un desafiament important en les xarxes mòbils que actualment está rebent molta atenció és aconseguir que la xarxa siga capaç de gestionar escenaris d'accés massiu en què una gran quantitat de dispositius utilitzen comunicacions M2M. D'altra banda, els sistemes mòbils han experimentat un gran desenvolupament en les últimes dècades: incorporen tecnologia sofisticada i nous algoritmes per oferir una àmplia gamma de serveis. El modelatge i análisi del rendiment d'aquestes xarxes multiservei és també un desafiament important que podria requerir un gran esforç computacional. Per abordar els desafiaments anteriors, en aquesta tesi doctoral ens centrem en primer lloc en el disseny i l'avaluació de les prestacions de nous mecanismes de control d'accés per fer front a les comunicacions massives M2M en xarxes cel · lulars. Posteriorment ens ocupem de l'avaluació de prestacions de xarxes multiservei i proposem una nova tècnica analítica que ofereix precisió i eficiència computacional. El nostre principal objectiu és proporcionar solucions per a alleujar la congestió a la xarxa d'accés ràdio quan un gran nombre de dispositius M2M intenten connectar-se a la xarxa. Considerem els dos tipus d'escenaris següents: (i) els dispositius M2M es connecten directament a les estacions base cel · lulars, i (ii) formen grups i les dades s'envien a concentradors de trànsit (gateways) que els proporcionen accés a la infraestructura. En el primer escenari, atès que el nombre de dispositius afegits a la xarxa augmenta contínuament, aquesta hauria de ser capaç de gestionar el considerable increment en les sol · licituds d'accés. El 3rd Generation Partnership Project (3GPP) ha proposat l'access class barring (ACB) com una solució pràctica per al control de congestió a la xarxa d'accès ràdio i la xarxa troncal. L'ajust correcte dels paràmetres d'ACB d'acord amb la intensitat del trànsit és crític, però com fer-ho de forma dinàmica i autònoma és un problema complex, la solució del qual no està recollida en les especificacions del 3GPP. Aquesta tesi doctoral contribueix a l'anàlisi del rendiment i al disseny de nous algoritmes que implementen efectivament aquest mecanisme, i així superar els desafiaments introduïts per les comunicacions massives M2M en les xarxes mòbils actuals i futures. En el segon escenari, atès que l'heterogeneïtat dels dispositius IoT i les arquitectures cel · lulars basades en hardware imposen desafiaments encara més grans per permetre una comunicació flexible i eficient en els sistemes sense fil 5G, aquesta tesi doctoral també contribueix al disseny de software-defined gateways (SD-GWS) en una nova arquitectura proposada per a xarxes sense fils definides per programari que s'anomena SoftAir. Això permet gestionar tant un gran nombre de dispositius com el volum de dades que estaran abocant a la xarxa. Una altra contribució d'aquesta tesi doctoral és la proposta d'una tècnica innovadora per a l'anàlisi de prestacions de xarxes multiservei d'alta capacitat que es basa en un nou enfocament del modelitzat analític de sistemes que operen a diferents escales temporals. Aquest enfocament utilitza l'anàlisi del transitori d'una sèrie de subcadenes absorbents i l'anomenem absorbing Markov chain Approximation (AMCA). Els nostres resultats mostren que per a un cost computacional donat, AMCA calcula els paràmetres de prestacions habituals d
Tello Oquendo, LP. (2018). Design and Performance Analysis of Access Control Mechanisms for Massive Machine-to-Machine Communications in Wireless Cellular Networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/107946
TESIS

The exponential increase of mobile users and the demand for high-speed data services has resulted in significant congestions in cellular backhaul capacity. As a solution to satisfy the traffic requirements of the existing 4G network, the 5G network has emerged as an enabling technology and a fundamental building block of next-generation communication networks. An essential requirement in 5G backhaul networks is their unparalleled capacity to handle heavy traffic between a large number of devices and the core network. Microwave and optic fiber technologies have been considered as feasible solutions for next-generation backhaul networks. However, such technologies are not cost effective to deploy, especially for the backhaul in high-density urban or rugged areas, such as those surrounded by mountains and solid rocks. Additionally, microwave technology faces alarmingly challenging issues, including limited data rates, scarcity of licensed spectrum, advanced interference management, and rough weather conditions (i.e., rain, which is the main weather condition that affects microwave signals the most). The focus of this work is to investigate the feasibility of using free-space-optical (FSO) technology in the 5G cellular backhaul network. FSO is a cost-effective and wide-bandwidth solution as compared to traditional backhaul solutions. However, FSO links are sensitive to atmospheric turbulence-induced fading, path loss, and pointing errors. Increasing the reliability of FSO systems while still exploiting their high data rate communications is a key requirement in the deployment of an FSO backhaul network. Overall, the theoretical models proposed in this work will be shown to enhance FSO link performance. In the experimental direction, we begin by designing an integrated mobile FSO system. To the best of our knowledge, no work in the literature has addressed the atmospheric path loss characterization of mobile FSO channels in a coastal environment. Therefore, we investigate the impact of weather effects in Thuwal, Saudi Arabia, over FSO links using outdoor and indoor setups. For the indoor experiments, results are reported based on a glass climate chamber in which we could precisely control the temperature and humidity.

As fifth generation (5G) standards have been established and 5G commercial products are just around the corner, both academia and industry have started to look at requirements for beyond 5G networks. Network flexibility and long battery life are among the key requirements for beyond 5G wireless communication systems. These critical requirements, which have not been sufficiently addressed in the previous generations, are the focus of this thesis. The first half of this thesis explores two important use cases of drones to provide flexible communication networks. First, the performance of a cellular network with underlay drone cell for temporary events inside a stadium is studied. Using stochastic geometry, a general analytical framework is proposed to analyze the uplink and the downlink coverage probabilities for both the aerial and the terrestrial systems. Our results show that for urban environment and dense urban environment, the drone is best deployed at a low height (e.g., 200 m or lower), regardless of the distance between the center of the stadium and the terrestrial base station. However, for suburban environment and high-rise urban environment, the best drone altitude varies. Second, the performance of emergency information dissemination in public safety scenarios using drone is studied. A drone-assisted multihop multicast device-to-device (D2D) network is considered, where an emergency alert message broadcasted by a drone at the first time slot is multicasted by the D2D users that have successfully received the message through multihop. The impact of different system parameters on the link and the network performance is investigated. Our results demonstrate that a higher drone altitude provides better link and network coverage probabilities and lower mean local delay. Under practical setups, the cell edge user located 2 km from the ground projection of the drone has a link coverage probability around 90% after 5 time slots and a mean local delay of 2.32 time slots with a drone height as low as 200 m. The second half of this thesis investigates wireless power transfer networks. Specifically, the use of power beacons in a millimeter wave wireless ad hoc network is considered, where transmitters adopt the harvest-then-transmit protocol. First, the characteristic of the aggregate received power from power beacons is analyzed and the lognormal distribution is found to provide the best complementary cumulative distribution function approximation compared to other distributions considered in the literature. Then, a tractable model with discrete transmit power for each transmitter is proposed to compute the channel coverage probability and the total coverage probability. Our results show that our model provides a good accuracy and reveal the impact of different system parameters on the total coverage probability. Our results also illustrate that under practical setups, for power beacon transmit power of 50 dBm and transmitters with maximum transmit power between 20 - 40 dBm, which are safe for human exposure, the total coverage probability is around 90%. Thus, it is feasible and safe to power transmitters in a millimeter wave ad hoc network using power beacons.

Il 5G sta compiendo una trasformazione significativa del panorama delle reti mobili, introducendo capacità flessibili ed eterogenee che coordinano armoniosamente numerose componenti tecniche dal momento che sono attualmente in fase di sviluppo una grande varietà di servizi avanzati, ognuno dei quali caratterizzato da requisiti diversi. Di conseguenza, appare naturale come il 5G non abbia un'unica interfaccia radio, bensì una famiglia di interfacce radio, tutte opportunamente inserite in un unico framework comune, al fine di rispondere adeguatamente ai diversi casi d'uso. Tuttavia, la gestione efficace di una così ampia diversità è un obiettivo estremamente ambizioso da raggiungere. A tal scopo, questo lavoro si pone l'obiettivo di studiare, analizzare e presentare modelli di simulazione, nonché procedure di gestione all’avanguardia delle reti di accesso 5G & Beyond. In particolare, in questa tesi si propone un simulatore system-level ed open source per modellare gli elementi chiave della rete di accesso 5G e supportare quindi l'analisi delle prestazioni di diversi scenari di riferimento. Inoltre, si disamina la NarrowBand IoT, considerata una tecnologia di accesso radio particolarmente promettente per soddisfare i requisiti dello sviluppo 5G & Beyond in ambito Internet of Things (IoT). Infine, si pone un accento sul problema del RAN Slicing sfruttando l'Edge Computing e l'Intelligenza Artificiale, che promettono di trasformare le future reti mobili in infrastrutture che tengano in considerazione i servizi e il canale radio.
5th Generation (5G) is providing a significant transformation in the mobile network landscape. It introduces flexible and heterogeneous capabilities to harmoniously blend numerous technical components since a variety of advanced services are being developed, each one entailing different requirements. For this reason, 5G does not have a single air interface, but rather a family of air interfaces to adequately address specific use cases, all plugged into a common framework. Nonetheless, the effective management of such a broad diversity is an extremely ambitious goal to accomplish. To this end, this work pursues the goal of investigating several cutting-edge management techniques and simulation models for 5G & Beyond Radio Access Networks (RANs). Specifically, this thesis presents an open-source system-level tool to model the key elements of the 5G RAN and support the performance analysis of reference scenarios. Moreover, it examines NarrowBand IoT (NB-IoT), which is usually regarded as a promising radio access technology to meet the requirements of the 5G & Beyond development for the Internet of Things (IoT). Finally, it addresses the RAN Slicing problem leveraging Edge Computing and Artificial Intelligence (AI), which promise to turn future mobile networks into service- and radio-aware infrastructures.

The demand for wireless communication is ceaselessly increasing in terms of the number of subscribers and services. Future generations of cellular networks are expected to allow not only humans but also machines to be immersively connected. However, the radio frequency spectrum is already fully allocated. Therefore, developing techniques to increase spectrum efficiency has become necessary. This dissertation analyzes two spectrum sharing techniques that enable efficient utilization of the available radio resources in cellular networks. The first technique, called full-duplex (FD) communication, uses the same spectrum to transmit and receive simultaneously. Using stochastic geometry tools, we derive a closed-form expression of an upper-bound for the maximum achievable uplink ergodic rate in FD cellular networks. We show that the uplink transmission is vulnerable to the new interference introduced by FD communications (interference from the downlink transmission in other cells), especially when the disparity in transmission power between the uplink and downlink is considerable. We further show that adjusting the uplink transmission power according to the interference power level and the channel gain can improve the uplink performance in full-duplex cellular networks. Moreover, we propose an interference management technique that allows a flexible overlap between the spectra occupied by the downlink and uplink transmissions. The flexible overlap is optimized along with the user-to-base station association, the power allocation and the channel allocation in order to maximize a network-wide utility function. The second spectrum sharing technique, called non-orthogonal multiple access (NOMA), allows a transmitter to communicate with multiple receivers through the same frequency-time resource unit. We analyze the implementation of such a scheme in the downlink of cellular networks, more precisely, in the downlink of fog radio access networks (FogRANs). FogRAN is a network architecture that takes full advantage of the edge devices capability to process and store data. We propose managing the interference for NOMA-based FogRAN to improve the network performance by jointly optimizing user scheduling, the power allocated to each resource block and the division of power between the multiplexed users. The simulation results show that significant performance gains can be achieved through proper resource allocation with both studied spectrum sharing techniques.

With the recent advancements in wireless communication, there has been tremendous growth in the applications such as body area communication, vehicular communication and device-to-device (D2D) communication etc. In most of these future generation applications, the data is transferred from source to destination through a wireless link. The signal experience many phenomena like reflection, refraction, diffraction and scattering in its path traveling from transmitter (Tx) to receiver (Rx). These phenomena result in the fluctuations in the received signal strength which eventually degrades the quality of the signal and is termed as fading. Fading can be classified as small-scale fading and large-scale fading. To characterize the small-scale fading and large-scale fading, different mathematical models are used in literature. The size of the mobile cells in third/fourth generation (3G/4G) wireless technologies was relatively large, thus the signal propagation scenario was thought to be outdoor propagation and various models such as Rayleigh, Rician, Nakagami, Weibull etc. were used to model that scenario. One of the main objectives of the fifth generation (5G) wireless networks is to provide high throughput and low latency to all users anywhere within the coverage area. However, because of the high attenuation provided by the structures' walls, delivering reliable services to consumers inside the buildings remains a serious challenge. The creation of a heterogeneous cellular network, in which a macro-cell is overlaid over a number of femtocells, dedicated to providing coverage for indoor users, is an effective approach that has recently been embraced by numerous standards. Femtocells are small, vi low power cellular BS, which can be installed in a small business environment or a home to provide better coverage with improved battery life for the mobile stations. Due to the small areas of the femtocells, the characterization of the signal cannot be modeled in the form of traditional outdoor propagation models. For addressing the propagation phenomenon in 5G and beyond technology, Beaulieu-Xie (BX) and Fisher-Snedecor F (FSF) distributions are introduced. The BX fading channel has found application in the signal propagation in small buildings and fast-moving trains. FSF fading channel is a composite fading model that is used to model the signal propagation for D2D and wearable communication links. The performance of communication system inside the densely packed small cells or femtocells with maximum ratio combining (MRC) diversity is studied. The closed-form expressions for outage probability (Pout), amount of fading (AF) and average symbol error probability (ASEP) for coherent and non-coherent modulation schemes are derived for the said channel. Further, the channel capacity (CC) analysis over different transmission policies is performed and the corresponding results are plotted. The effect of diversity on the performance measures are demonstrated. In contrary to Shannon’s ergodic capacity, the delay-constrained effective rate is used to define the maximum data rate of the real-time applications in 5G and beyond networks. We have studied the effective throughput performance of the multi-antenna system over the BX fading channel and FSF fading channel. The closed-form mathematical expressions for the effective capacity (EC) are derived in terms of Meijer-G function and the effect of different fading parameters on the effective throughput of the system is vii demonstrated. The simplified asymptotic expression for high signal-to-noise ratio (SNR) and low SNR regimes is provided to gain more insight in to the system. The intelligent reflecting surfaces (IRS) is a newer technology that is being used in 5G and beyond networks to improve the system performance. Due to this, the IRS-aided systems have been actively investigated. The application of the derived formulation for the IRS-aided system over the BX and SFS channels are studied. Interesting results of the system performance in terms of channel parameters are demonstrated. For the expressions having infinite series representation, the truncation error has been provided wherever possible. The effect of fading parameters on the performance measures are demonstrated through analytical results. Simulation results are corroborated along with the numerical results to verify the correctness of the proposed formulations. The results presented in this study can be used in designing the communication systems for real-time applications in next-generation wireless networks.