Letteratura scientifica selezionata sul tema "Beyond 5G Networks"

5G networks and beyond are expected to meet numerous service requirements in various aspects of our daily lives. At the same time, the functional complexity of 5G telecommunication networks increases by an order of magnitude compared to existing networks. 5G data rates are dramatically faster, connection density is higher, and latency is much lower, among other improvements. An efficient 5G network cannot be complete without incorporating artificial intelligence (AI) techniques. All this requires the use of new technologies, including artificial intelligence, to ensure the stable operation of telecommunication networks, methodology, system analysis, and key results. Scientific tasks for 5G communication networks are identified where the use of artificial intelligence, including machine and deep learning, seems appropriate. Practical Relevance. The results of the work may be useful in training in networks and telecommunication systems and in defining new scientific tasks for PhD students.

<p>With the advent of 5G networks, various research on Multi-access Edge Computing (MEC) to provide high-reliability and ultra-low latency services are being actively conducted. MEC is an intelligent service distributed cloud technology that provides a high level of personal services by deploying cloud servers to edge networks physically closed to users. However, there is a technical issue to be solved, e.g., the service being used by a user does not exist in the new edge network, and there may even be situations in which the service cannot be provided in the new edge network. To address this, the service application must be relocated according to the location of the user&rsquo;s movement. Various research works are underway to solve this service relocation issue, e.g., cold/live migration studies have been carried in legacy cloud environments. In this paper, we propose a container migration technique that guarantees a smooth service application relocation for mobile users. We design scenarios for adaptive handoff and describe the detailed operation process. In addition, we present our MEC testbed, which has been used to experiment our container migration technique.</p> <p>&nbsp;</p>

Device-to-device (D2D) communication is a promising paradigm for the fifth generation (5G) and beyond 5G (B5G) networks. Although D2D communication provides several benefits, including limited interference, energy efficiency, reduced delay, and network overhead, it faces a lot of technical challenges such as network architecture, and neighbor discovery, etc. The complexity of configuring D2D links and managing their interference, especially when using millimeter-wave (mmWave), inspire researchers to leverage different machine-learning (ML) techniques to address these problems towards boosting the performance of D2D networks. In this paper, a comprehensive survey about recent research activities on D2D networks will be explored with putting more emphasis on utilizing mmWave and ML methods. After exploring existing D2D research directions accompanied with their existing conventional solutions, we will show how different ML techniques can be applied to enhance the D2D networks performance over using conventional ways. Then, still open research directions in ML applications on D2D networks will be investigated including their essential needs. A case study of applying multi-armed bandit (MAB) as an efficient online ML tool to enhance the performance of neighbor discovery and selection (NDS) in mmWave D2D networks will be presented. This case study will put emphasis on the high potency of using ML solutions over using the conventional non-ML based methods for highly improving the average throughput performance of mmWave NDS.

Fifth-generation (5G) technology will play a vital role in future wireless networks. The breakthrough 5G technology will unleash a massive Internet of Everything (IoE), where billions of connected devices, people, and processes will be simultaneously served. The services provided by 5G include several use cases enabled by the enhanced mobile broadband, massive machine-type communications, and ultra-reliable low-latency communication. Fifth-generation networks potentially merge multiple networks on a single platform, providing a landscape for seamless connectivity, particularly for high-mobility devices. With their enhanced speed, 5G networks are prone to various research challenges. In this context, we provide a comprehensive survey on 5G technologies that emphasize machine learning-based solutions to cope with existing and future challenges. First, we discuss 5G network architecture and outline the key performance indicators compared to the previous and upcoming network generations. Second, we discuss next-generation wireless networks and their characteristics, applications, and use cases for fast connectivity to billions of devices. Then, we confer physical layer services, functions, and issues that decrease the signal quality. We also present studies on 5G network technologies, 5G propelling trends, and architectures that help to achieve the goals of 5G. Moreover, we discuss signaling techniques for 5G massive multiple-input and multiple-output and beam-forming techniques to enhance data rates with efficient spectrum sharing. Further, we review security and privacy concerns in 5G and standard bodies’ actionable recommendations for policy makers. Finally, we also discuss emerging challenges and future directions.

The concept of revolutionizing 5G (Fifth Generation) networks through a synergy of routing, clustering, and energy optimization is indeed a promising approach to enhancing the performance and lifespan of wireless networks. Exciting changes will occur in the physical, digital, and biological worlds over the next ten years. Although the needs for Beyond 5G (B5G) are not yet fully understood, an effort has been made to stratify 5G progression and B5G. This work highlights the focus on revolutionizing 5G networks through the integration of routing, clustering, and energy optimization techniques. By combining these methodologies, this research work aims to address the complex challenges in 5G networking, such as efficient data routing, resource allocation, and energy consumption. The objective is to achieve both exceptional performance and an extended lifespan for these networks. The proposed work holds promise for significantly enhancing the capabilities of 5G networks, resulting in improved user experiences, optimized resource utilization, and prolonged network lifespan. In order to completely meet the most stringent 5G standards, such as stratification, or deconstruction into existing technologies, will comprise technology scenarios of 5G evolutions. Wireless sensor networks (WSNs), which offer essential data collecting and monitoring capabilities, are made up entirely of 5G networks. These methods are designed specifically for use in 5G networks to increase the network’s lifespan and overall performance. For 5G networks, routing and clustering techniques from WSNs can be modified and optimized to increase energy efficiency and prolong the network lifetime in 5G networks.

The concept of revolutionizing 5G (Fifth Generation) networks through a synergy of routing, clustering, and energy optimization is indeed a promising approach to enhancing the performance and lifespan of wireless networks. Exciting changes will occur in the physical, digital, and biological worlds over the next ten years. Although the needs for Beyond 5G (B5G) are not yet fully understood, an effort has been made to stratify 5G progression and B5G. This work highlights the focus on revolutionizing 5G networks through the integration of routing, clustering, and energy optimization techniques. By combining these methodologies, this research work aims to address the complex challenges in 5G networking, such as efficient data routing, resource allocation, and energy consumption. The objective is to achieve both exceptional performance and an extended lifespan for these networks. The proposed work holds promise for significantly enhancing the capabilities of 5G networks, resulting in improved user experiences, optimized resource utilization, and prolonged network lifespan. In order to completely meet the most stringent 5G standards, such as stratification, or deconstruction into existing technologies, will comprise technology scenarios of 5G evolutions. Wireless sensor networks (WSNs), which offer essential data collecting and monitoring capabilities, are made up entirely of 5G networks. These methods are designed specifically for use in 5G networks to increase the network’s lifespan and overall performance. For 5G networks, routing and clustering techniques from WSNs can be modified and optimized to increase energy efficiency and prolong the network lifetime in 5G networks.

Fifth-generation (5G) technologies enable a wide range of vertical applications by connecting heterogeneous equipment and machines, resulting in significantly improved service quality, increased network capacity, and improved system performance. As a result, the world is shifting to 5G wireless networks. Because 5G has the advantage of supporting various vertical applications, 5G systems must still overcome challenges such as transparency, data interoperability probabilities, decentralization, and network privacy. In this paper, we'll show how blockchain can be used to solve problems in 5G, as well as some of the idea’s researchers, have come up with to solve them, like resource sharing, security, and mobility.

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

Abstract5G is the fifth generation of broadband cellular network and beyond 5G can be the 6G, which will be the sixth generation of broadband cellular network. Even though studies about 5G are still evolving, 6G has become a hot topic for cellular researchers these days. The expansion in the field of 5G and 6G is still in infancy stage as many problems still need to be solved. Out of these, security of data transmission is a premier concern. Therefore, cybersecurity is becoming increasingly important for these cellular networks. This paper is focused upon providing the in-depth overview of 5G and B5G networks. The paper aims to evaluate the insights of the security services of 6G networks and outlines various data security techniques used by 5G networks. The paper also provides introduction to quantum computing for cryptography and evaluates various post-quantum cryptography techniques. Finally, some novel research trends and directions in correlation of security of 5G and beyond 5G networks are listed to guide further research in the area.

AbstractSecurity of data is very important while providing communication either by the wired or wireless medium. It is a very challenging issue in the world and the wireless mobile network makes it more challenging. In a wireless mobile network, there is a cluster of self-contained, self-organized networks that form a temporarily multi-hop peer-to-peer radio network, lacking any use of the pre-determined organization. As these networks are mobile and wireless connection links are used to connect these networks through each other, many of the times these kinds of networks are accomplished of self-manage, self-define, and self-configure. Due to their dynamic nature, wireless mobile networks/systems do not have a fixed infrastructure and, due to this, it is more vulnerable to many types of hostile attacks. Different kinds of security attacks that are present in wireless mobile networks are stated in the paper with their spotting and precaution techniques. Furthermore, the paper deliberates on the various types of mobile networks along with their numerous challenges and issues. Moreover, the paper defines the need and goals of security in wireless mobile networks as well as many security attacks along with their detection or prevention methods.

AbstractThe significant expansion of cellular networks has increased their potential to support a wide range of use cases beyond their original purpose of providing broadband access. One such development is using cellular networks to support the Internet of Things (IoT), called Cellular IoT (CIoT). The growth of CIoT is an important trend in the evolution of cellular networks, it leads to broader and more comprehensive ecosystem circumstances. The extensive IoT business evolution is transforming a diverse sector, including health, smart cities, security, and agriculture. Nevertheless, a large scale with very different characteristics and use cases struggle with connectivity challenges due to the unique traffic features of massive IoT and the tremendous density of IoT devices. This study aims to identify the critical obstacles that hinder the widespread deployment of IoT over cellular networks and suggest an innovative algorithm to mitigate them effectively. We discovered that the primary challenges revolve around three specific areas: connection setup, network resource management, and energy consumption. In this regard, we investigate the integration of massive Machine-Type Communication (mMTC) into cellular networks, focusing on the performance of Narrowband IoT (NB-IoT) in supporting mMTC.

AbstractA widespread deployment of 5G technology with the Internet of Things (IoT) will be there in future years. The implementation of 5G technology perhaps becomes fortuitous for IoT as IoT has different variants of applications in the field of tracking data, and security systems. It is also applicable to applications like smart cities and smart buildings etc. Further, the introduction of the new frequency band in the present communication system gardened the interest of researchers in the area of optimization of energy in a mobile environment with dense traffic. This paper aims to represent the basics of 5G system along with IoT implementations. Also different techniques for energy efficiency are comparatively analyzed with their pros and cons for mobile wireless sensor networks.

AbstractThe use of previous generation networks like 4G was vastly used in the Internet of Things (IoT) devices. The constant need to grow and develop just so the network can fulfill the requirement of IoT devices is still going on. The exponential growth of the data services substantially challenged the security and the networks of IoT because they were run by the mobile internet requiring high bit rate, low latency, high availability, and performances within various networks. The IoT integrates several sensors and data to provide services and a communication standard. Fifth Generation Communication System (5G) enabled IoT devices to allow the seamless connectivity of billions of interconnected devices. Cellular connections have become a central part of the society that powers our daily lives. Numerous security issues have come to light because of the exponential expansion of 5G technologies and the adaptation of the slow counterpart of IoT devices. Network services without security and privacy pose a threat to the infrastructure and sometimes endanger human lives. Analyzing security threats and mitigation is a crucial and fundamental part of the IoT ecosystem. Authorization of data, confidentiality, trust, and privacy of 5G enabled IoT devices are the most challenging parts of the system. And to provide a solution to these, we need a robust system to handle cyberattacks and prevent vulnerabilities by countermeasures. This paper includes a comprehensive discussion of 5G, IoT fundamentals, the layered architecture of 5G IoT, security attacks and their mitigation, current research, and future directions for 5G enabled IoT infrastructure.

AbstractThe ultrafast 5G network will play a significant role in the farming industry over the upcoming couple of years, serving to boost crop yield and quality while requiring minimal labour. Farmers will be more informed to make smart decisions regarding irrigation by using smart and precision farming. The introduction of 5G will significantly alter the farming characteristics and agriculture practices in this era of Agriculture 4.0. 5G network’s IoT-based cloud computing service offers smart farming solutions that are both flexible and resourceful. This will permit the seamless operation of various unmanned agricultural devices during ploughing, sowing seed and managing phases of crop farming, resulting in secure, dependable, environment-friendly and energy-efficient operations, as well as the creation of unmanned farms. This paper examines the need for and role of smart and precision farming in the agricultural sector incorporating 5G applications in precision farming in the present era of Agriculture 4.0, such as real-time monitoring, data analytics, cloud repositories, virtual consultation and predictive maintenance and also discusses upcoming opportunities. 5G-based IoT solutions focusing towards Ultra-Reliable Low Latency Communication (URLLC) like automated control and self-driven vehicles to support rapid response times and higher dependability will diminish communication delays in time-sensitive agriculture applications and non-public networks to allocate part of frequency spectrum on demand, network slicing alternatives are also discussed here.

Wireless communications are rapidly taking an important role in factory environment. The current Wi-Fi technologies struggle to meet the requirements of industrial factories, for example with regard to latency and security. The emerging 5G communication networks are the first networks expected to meet such requirements. Private networks are owned by the factories themselves. Private networks can utilize 5G technologies to tailor the networks to meet the exact demands within the factory environment and guarantee that the factories can use the whole bandwidth for their own use. This concurrently increases the data security as the data does not need to be deliveved over public networks. This paper describes the latest developments in 5G with regard to private networks and Industry 4.0, which is the name given to the digitalization, automatization and data exchange trend currently ongoing in factory environments. In this paper we describe a private cellular network we have installed inside a factory building. This network has been trialed with wireless pyrometer measurement data transmission and environmental surveillance of a measurement laboratory. This paper analyses the suitability of private networks for these use cases and discusses in general which applications would benefit the most from private wireless networks.

Deploying and operating optical transport networks is a complex task. This paper presents a few challenges operators must tackle when considering 5G and beyond scenarios and the lesson learned by addressing them.