Le problème de coloration de graphe est un problème NP-complet particulièrement étudié, qui permet de modéliser de problèmes dans des domaines variés. Dans cette thèse, de nouveaux algorithmes exacts basés sur une étude de la structure du graphe sont proposés. Ce travail s'appuie sur l'algorithme « Total solutions Exact graph Coloring » (TexaCol) qui construit toutes les solutions en exploitant l'ensemble des cliques d'un graphe. Deux algorithmes exacts, « Partial best solutions Exact graph Coloring » (PexaCol) et « All best solutions Exact graph Coloring » (AexaCol), sont présentés ici pour construire certaines solutions optimales ou toutes les meilleures solutions. Ces deux algorithmes utilisent la méthode de backtracking, dans laquelle ils ne choisissent que les sous-ensembles de meilleurs solutions pour continuer la coloration. L’analyse de résultat montre que PexaCol et AexaCol sont capables de traiter des graphes plus grands que TexaCol. Mais surtout, AexaCol trouve toutes les meilleures solutions significativement plus vite que TexaCol ainsi que le solveur Gurobi, qui sont utilisés comme référence.La téléphonie mobile est un domaine en plein essor qui peut s'appuyer sur une modélisation à base de graphes. Actuellement, les techniques de type « Device-to-Device » (D2D) prennent une place importante dans les réseaux mobiles. L’allocation de ressource constitue l'un des principaux problèmes en matière de performance. Pour assigner efficacement une ressource radio à une paire D2D dans le système Long-Term Evolution (LTE), un schéma systématique d'allocation de ressources est proposé dans cette thèse. Il est basé sur une clusturisation des liens D2D, et permet de prendre en compte à la fois l'allocation inter-cluster et intra-cluster des ressources. En déterminant les zones d'interférence, le problème d'allocation des ressources inter-cluster est formulé comme un problème de coloration de graphe dynamique. Un algorithme de coloration de graphe dynamique est ainsi proposé, basé sur PexaCol. Cet algorithme peut assigner les ressources radio aux clusters qui sont générés ou supprimés dynamiquement. L’analyse numérique montre que cet algorithme assure une bonne performance en termes d'utilisation des ressources, de temps d’exécution et d'adaptabilité. Concernant le problème d’allocation de ressources inter-cluster, une méthode fondée sur la topologie est proposée, intégrant naturellement l'allocation de puissance et l’allocation de Resource Block (RB). Pour simplifier ce problème d'allocation de ressources, la meilleure topologie est choisie à chaque étape, celle qui permet d'obtenir le meilleur débit en utilisant le moins de RBs. A partir de ce procédé, quatre algorithmes d'optimisation sont proposés: l’algorithme glouton statique, PexaCol statique, PexaCol dynamique et PexaCol dynamique approximatif. L'analyse des résultats montre que pour les petits clusters, les versions statiques et dynamiques de PexaCol permettent d'obtenir un index d’optimisation maximal en choisissant la meilleure topologie locale pour chaque noeud. A l'opposé, les algorithmes "glouton statique" et "PexaCol dynamique approximatif" permettent d'obtenir une solution sous-optimale pour l'optimisation locale avec une complexité moindre. Pour les grands clusters, avec certaine séquence de la coloration, le PexaCol dynamique approximatif est mieux que l’algorithme glouton statique pour l’index d’optimisation pendant un temps d’exécution acceptable. / Graph coloring problem is a famous NP-complete problem, which has extensive applications. In the thesis, new exact graph coloring algorithms are researched from a graph structure point of view. Based on Total solutions Exact graph Coloring algorithm (TexaCol) which is capable of getting all coloring solution subsets for each subgraph, two other exact algorithms, Partial best solutions Exact graph Coloring algorithm (PexaCol) and All best solutions Exact graph Coloring algorithm (AexaCol), are presented to get multiple best solutions. These two algorithms utilize the backtracking method, in which they only choose the best solution subset each step to continue the coloring until partial or all best solutions are obtained. The result analysis shows that PexaCol and AexaCol can deal with larger graphs than TexaCol and especially, AexaCol runs much faster than TexaCol and the solver Gurobi to get all best solutions.Device-to-Device (D2D) is a promising technique for the future mobile networks, such as 5th generation wireless systems (5G), and the resource allocation is one of the most crucial problems for its performance. In order to efficiently allocate radio resource for D2D links in Long-Term Evolution (LTE) system, a systematic resource allocation scheme is proposed based on D2D clusters, including the inter-cluster resource allocation and the intra-cluster resource allocation. With the cluster interference range, the inter-cluster resource allocation problem is formulated as a dynamic graph coloring problem, and a dynamic graph coloring algorithm is designed based on PexaCol. This algorithm is able to allocate radio resource to clusters while they are dynamically generated and deleted. The numerical analysis results show that this algorithm has good performance in resource utilization, runtime and scalability.For the intra-cluster resource allocation problem, a topology-based resource allocation method is designed naturally combining power allocation with Resource Block (RB) allocation. To simplify this associated optimization problem, a local optimal method is proposed, in which the best topology is chosen each step achieving the maximal throughput with the minimum number of assigned RBs. With respect to this method, four algorithms are presented: static greedy, static PexaCol, dynamic PexaCol and dynamic PexaCol approximate. Result analysis shows that for small-scale clusters, static PexaCol and dynamic PexaCol are capable of getting a maximal optimization index by locally choosing the best topology for each node while static greedy and dynamic PexaCol approximate are able to get the suboptimal solution for the local optimization with much lower complexity. For large-scale clusters, giving certain treating sequences, the dynamic PexaCol approximate performs better than static greedy regarding the optimization index within an acceptable runtime.

Cette thèse porte sur plusieurs technologies de déchargement cellulaire pour les futurs réseaux sans fil avec l’amélioration envisagée sur la efficacité spatiale du spectre et l’efficacité énergétique. Notre recherche concerne deux directions principales, y compris la communication D2D underlaid dans les réseaux cellulaires et le caching proactif au bord de réseau.La première partie de cette thèse contient deux chapitres qui présentent nos résultats de recherche sur les réseaux cellulaire avec D2D underlaid. Notre recherche se focalise sur l’accès opportuniste distribué, dont la performance en termes du débit D2D est optimisé dans deux scénarios: 1) en supposant que l’utilisateur cellulaire avec un trafic saturé peut avoir une probabilité de couverture minimale; 2) en supposant que le trafic discontinu à l’utilisateur cellulaire, dont le délai moyen doit être maintenue au-dessous d’un certain seuil. La deuxième partie de cette thèse se focalise sur les méthodes de caching proactif au bord de réseau, y compris le caching aux petites cellules et aux appareils des utilisateurs. Tout d’abord, nous étudions le placement de contenu probabiliste dans différents types de réseaux et avec différents objectifs d’optimisation. Deuxièmement, pour le caching aux petites cellules, nous proposons un schéma coopérative parmi les petites stations de base, qui exploite le gain combiné du caching coopérative et les techniques de multipoint coordonnée. Les modèles de processus ponctuel nous permet de créer la connexion entre la diversité de transmission en couche PHY et la diversité de contenus stockés. / This thesis focuses on several emerging technologies towards future wireless networks with envisaged improvement on the area spectral efficiency and energy efficiency. The related research involves two major directions, including deviceto- device (D2D) communication underlaid cellular networks and proactive caching at network edge. The first part of this thesis starts with introducing D2D underlaid cellular network model and distributed access control methods for D2D users that reuse licensed cellular uplink spectrum. We aim at optimize the throughput of D2D network in the following two scenarios: 1) assuming always backlogged cellular users with coverage probability constraint, 2) assuming bursty packet arrivals at the cellular user, whose average delay must be kept below a certain threshold. The second part of this thesis focuses on proactive caching methods at network edge, including at small base stations (SBSs) and user devices. First, we study and compare the performance of probabilistic content placement in different types of wireless caching networks and with different optimization objectives. Second, we propose a cooperative caching and transmission strategy in a cluster-centric small cell networks (SCNs), which exploits the combined gain of cache-level cooperation and CoMP technique. Using spatial models from stochastic geometry, we build the connection between PHY transmission diversity and the content diversity in local caches.

Device-to-device (D2D) communications underlaying a cellular infrastructure takes advantage of the physical proximity of communicating devices and increasing resource utilisation. However, adopting D2D communications in complex scenarios poses substantial challenges for the resource allocation design. Meanwhile, matching theory has emerged as a promising framework for wireless resource allocation which can overcome some limitations of game theory and optimisation. This thesis focuses on the resource allocation optimisation for D2D communications based on matching theory. First, resource allocation policy is designed for D2D communications underlaying cellular networks. A novel spectrum allocation algorithm based on many-to-many matching is proposed to improve system sum rate. Additionally, considering the quality-of-service (QoS) requirements and priorities of di erent applications, a context-aware resource allocation algorithm based on many-to-one matching is proposed, which is capable of providing remarkable performance enhancement in terms of improved data rate, decreased packet error rate (PER) and reduced delay. Second, to improve resource utilisation, joint subchannel and power allocation problem for D2D communications with non-orthogonal multiple access (NOMA) is studied. For the subchannel allocation, a novel algorithm based on the many-to-one matching is proposed for obtaining a suboptimal solution. Since the power allocation problem is non-convex, sequential convex programming is adopted to transform the original power allocation problem to a convex one. The proposed algorithm is shown to enhance the network sum rate and number of accessed users. Third, driven by the trend of heterogeneity of cells, the resource allocation problem for NOMA-enhanced D2D communications in heterogeneous networks (HetNets) is investigated. In such a scenario, the proposed resource allocation algorithm is able to closely approach the optimal solution within a limited number of iterations and achieves higher sum rate compared to traditional HetNets schemes. Thorough theoretical analysis is conducted in the development of all proposed algorithms, and performance of proposed algorithm is evaluated via comprehensive simulations. This thesis concludes that matching theory based resource allocation for D2D communications achieves near-optimal performance with acceptable complexity. In addition, the application of D2D communications in NOMA and HetNets can improve system performance in terms of sum rate and users connectivity.

Device-to-Device (D2D) communication is one of the technologies for next generation communication system. Unlike traditional cellular network, D2D allows proximity users to communicate directly with each other without routing the data through a base station. The main aim of this study is to improve the overall energy efficiency (EE) of D2D communications overlaying cellular system. To reduce the complexity of joint EE optimization, we decompose the main EE problem into two subproblems; resource efficiency (RE) optimization in the first stage and EE optimization for D2D pairs in the second stage. Firstly, we propose an alternative two-stage RE-EE scheme for a single cellular user equipment (CUE) and a D2D pair utilizing uplink spectrum. Later, we extend this work for multiple CUEs and D2D pairs by considering the downlink orthogonal frequency division multiple access (OFDMA). By exploiting a range of optimization tools including the Bisection method, interior point algorithm, fractional programming, Dinkelbach approach, Lagrange dual decomposition, difference of convex functions, and concave-convex procedure, the original non-convex problems are solved and we present iterative two-stage RE-EE solutions. Simulation results demonstrate that the proposed two-stage scheme for uplink scenario outperforms the cellular mode and dedicated mode of communications and the performance is close to the global optimal solution. The results also show that the proposed schemes for downlink resource sharing provide improved system EE performance with significant gain on EE for D2D users compared to a two-stage EE-EE solution, which is obtained numerically. Furthermore, the RE and EE optimization for non-orthogonal multiple access (NOMA) are considered to study the effect of users' access to the whole spectrum. The results indicate that the proposed RE scheme for NOMA with D2D communications achieves higher system EE compared to the OFDMA based schemes.

Improving spectral-utilization is a core focus to cater the ever-increasing demand in data rate and system capacity required for the development of 5G. This dissertation focuses on three spectrum-reuse technologies that are envisioned to play an important role in 5G networks: device-to-device (D2D), full-duplex (FD), and nonorthogonal multiple access (NOMA). D2D allows proximal user-equipments (UEs) to bypass the cellular base-station and communicate with their intended receiver directly. In underlay D2D, the D2D UEs utilize the same spectral resources as the cellular UEs. FD communication allows a transmit-receive pair to transmit simultaneously on the same frequency channel. Due to the overwhelming self-interference encountered, FD was not possible until very recently courtesy of advances in transceiver design. NOMA allows multiple receivers (transmitters) to communicate with one transmitter (receiver) in one time-frequency resource-block by multiplexing in the power domain. Successive-interference cancellation is used for NOMA decoding. Each of these techniques significantly improves spectral efficiency and consequently data rate and throughput; however, the price paid is increased interference. Since each of these technologies allow multiple transmissions within a cell on a time-frequency resource-block, they result in interference within the cell (i.e., intracell interference). Additionally, due to the increased communication, they increase network interference from outside the cell under consideration as well (i.e., increased intercell interference). Real networks are becoming very dense; as a result, the impact of intercell interference coming from the entire network is significant. As such, using models that consider a single-cell/few-cell scenarios result in misleading conclusions. Hence, accurate modeling requires considering a large network. In this context, stochastic geometry is a powerful tool for analyzing random patterns of points such as those found in wireless networks. In this dissertation, stochastic geometry is used to model and analyze the different technologies that are to be deployed in 5G networks. This gives us insight into the network performance, showing us the impacts of deploying a certain technology into real 5G networks. Additionally, it allows us to propose schemes for integrating such technologies, mode-selection, parameter-selection, and resource-allocation that enhance the parameters of interest in the network such as data rate, coverage, and secure communication.

No description available.

Ericsson Brasil / Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / Em um mundo onde as pessoas contam com smartphone, smartwatch, tablet e outros dispositivos para mantÃ-las conectadas onde quer que vÃo, t odos esperam que seus aplicativos sejam executados sem problemas, tais como cham adas abandonadas, download lento e vÃdeos com saltos. Neste contexto, comunicaÃÃo dispositivo-a-dispositivo ( do inglÃs, Device-to-Device (D2D)) constitui uma tecnologia promissora, pois à um tipo de comun icaÃÃo direta e utiliza baixa potÃncia entre dispositivos prÃximos, permitindo-se desv iar o trÃfego da rede mÃvel, aumentar a eficiÃncia espectral e de potÃncia. Do ponto de vista do assi nante, D2D significa usar aplicaÃÃo sem problemas e aumentar o tempo de vida da bateria do celular. No entanto, a fim de realizar os ganhos potenciais das comunic aÃÃes D2D, algumas questÃes-chave devem ser abordadas, pois as comunicaÃÃes D 2D podem aumentar a interferÃncia co-canal e comprometer a qualidade do enlace das comunicaÃÃes celulares. Esta dissertaÃÃo foca em tÃcnicas de Gerenciamento de Recur sos de RÃdio (do inglÃs, Radio Resource Management (RRM)) para mitigar a interferÃncia co -canal para comunicaÃÃes D2D que se baseiam na EvoluÃÃo de Longo Prazo (do inglÃs, Long Ter m Evolution (LTE)), visando a reduÃÃo da interferÃncia intra- e inter-celular e na melho ria da eficiÃncia energÃtica. Os principais esquemas de Controle de PotÃncia (do inglÃs, Pow er Control (PC)) (e.g. OLPC,CLPC e SDPC) e um esquema hÃbrido (CLSD) sÃo calibrados e utilizad os no cenÃrio macro ou micro multicelular, usando diferentes cargas e InformaÃÃo do Est ado do Canal (do inglÃs, Channel State Information (CSI)) perfeita ou imperfeita. AlÃm diss o, o impacto da inclinaÃÃo da antena ( downtilt ) à analisado, que à usada para ajustar o raio de cobertura de u ma Evolved Node B (eNB) e reduzir a interferÃncia co-canal, aumentando o iso lamento de cÃlulas. Os resultados numÃricos indicam que os regimes de controle d e potÃncia e inclinaÃÃo da antena, devidamente calibrados, podem fornecer ganhos p ara a comunicaÃÃo celular e D2D. Em outras palavras, a tecnologia D2D pode ser utilizada para aumentar ainda mais a eficiÃncia de espectro e a eficiÃncia energÃtica se algoritm os de RRM forem utilizados adequadamente / In a world where people count on their smartphone, smartwatch, tablet and other devices to keep them connected wherever they go, they expect its application to run without problems, such as dropped calls, slow download and choppy videos. In this context, Device-to-Device (D2D) communication represents a promising technology, because it is a direct and low-power communication between devices close, allowing to offload the data transport network, increase spectral and power efficiency. From the subscriber point of view, D2D means to use applications without problem and increase battery life. However, in order to realize the potential gains of D2D communications, some key issues must be tackled, because D2D communications may increase the co-channel interference and compromise the link quality of cellular communications. This masterâs thesis focuses on Radio Resource Management (RRM) techniques, especially Power Control (PC) schemes, to mitigate the co-channel interference for D2D communications underlaying a Long Term Evolution (LTE) network, aiming at the reduction of the intra- and inter- cell interference and at the improvement of energy efficiency. The main PC schemes (e.g. OLPC, CLPC and SDPC) and a hybrid scheme (CLSD) are calibrated and used in macro- or micro- multicell scenario, using different loads and imperfect Channel State Information (CSI). In addition, the impact of downtilt is analyzed, which is used to adjust the coverage radius of an Evolved Node B (eNB) and reduce co-channel interference by increasing cell isolation. The numerical results indicate that PC schemes and downtilt, duly calibrated, can provide gains to cellular and D2D communications. In other words, D2D technology can be used to further increase the spectral and energy efficiency if RRM algorithms are used suitably.

<p>    </p> <p>In order to advance next-generation communication systems, it is critical to enhance the state-of-the-art communication architectures, such as device-to-device (D2D), multiple- input multiple-output (MIMO), and intelligent reflecting surface (IRS), in terms of achieving high data rate, low latency, and high energy efficiency. In the first part of this dissertation, we address joint learning and optimization methodologies on cutting-edge network archi- tectures. First, we consider D2D networks equipped with MIMO systems. In particular, we address the problem of minimizing the network overhead in D2D networks, defined as the sum of time and energy required for processing tasks at devices, through the design for MIMO beamforming and communication/computation resource allocation. Second, we address IRS-assisted communication systems. Specifically, we study an adaptive IRS control scheme considering realistic IRS reflection behavior and channel environments, and propose a novel adaptive codebook-based limited feedback protocol and learning-based solutions for codebook updates. </p> <p><br></p> <p>Furthermore, in order for revolutionary innovations to emerge for future generations of communications, it is crucial to explore and address fundamental, long-standing open problems for communications, such as the design of practical codes for a variety of important channel models. In the later part of this dissertation, we study the design of practical codes for feedback-enabled communication channels, i.e., feedback codes. The existing feedback codes, which have been developed over the past six decades, have been demonstrated to be vulnerable to high forward/feedback noises, due to the non-triviality of the design of feedback codes. We propose a novel recurrent neural network (RNN) autoencoder-based architecture to mitigate the susceptibility to high channel noises by incorporating domain knowledge into the design of the deep learning architecture. Using this architecture, we suggest a new class of non-linear feedback codes that increase robustness to forward/feedback noise in additive White Gaussian noise (AWGN) channels with feedback. </p>

Předkládaná disertační práce je zaměřena na "heterogenní propojení mobilních zařízení v bezdrátových systémech 5. generace". Navzdory nepochybnému pokroku v rámci navržených komunikačních řešení postrádají mobilní sítě nastupující generace dostatečnou šířku pásma a to hlavně kvůli neefektivnímu využívání rádiového spektra. Tato situace tedy v současné době představuje řadu otázek v oblasti výzkumu. Hlavním cílem této disertační práce je proto návrh nových komunikačních mechanismů pro komunikaci mezi zařízeními v bezprostřední blízkosti s asistencí mobilní sítě a dále pak návrh a implementace algoritmů pro dynamické přidělování frekvenčního spektra v nastupujících mobilních sítích 5G. Navrhnuté komunikační mechanismy a algoritmy jsou následně komplexně vyhodnoceny pomocí nově vyvinutých simulačních nástrojů (kalibrovaných s využitím 3GPP trénovacích dat) a zejména pak v experimentální mobilní síti LTE-A, která se nachází v prostorách Vysokého učení technického v Brně, Česká Republika. Získané praktické výsledky, které jsou podpořeny zcela novou matematickou analýzou ve speciálně navržených charakteristických scénářích, představují řešení pro vlastníka spektra v případě požadavků na jeho dynamické sdílení. Tato metoda tedy představuje možnost pro efektivnější využití spektra v rámci mobilních sítí 5G bez degradace kvality služeb (QoS) a kvality zážitků (QoE) pro koncové uživatele. Vědecký přínos dosažených výsledků dokazuje fakt, že některé z principů představených v této disertační práci byly zahrnuty do celosvětově uznávaného standardu (specifikace) 3GPP Release 12.

La recherche dans les réseaux de communication cherche à améliorer la capacité et les performances des technologies de réseaux tout en satisfaisant à la fois la demande croissante d’instantanéité des accès et des échanges d’information. Par exemple, les travaux sur les systèmes sans-fil de cinquième génération (5G) visent à augmenter le débit de données et l’efficacité spectrale mais aussi à réduire la latence et la consommation d’énergie. Dans ce contexte, la mise en réseau basée sur la proximité est envisagée afin d’améliorer l’échange d’information entre périphériques proches, même dans le cas où aucune infrastructure n’est disponible. Une composante essentielle de ces solutions est la capacité de rapidement détecter (ou découvrir) les autres systèmes à proximité. Bien que l’utilisation de la découverte des systèmes et de services ne soit pas à proprement parler une nouveauté dans les réseaux, son adoption dans les réseaux sans-fil a augmenté l’importance et la pertinence de ce type de mécanismes. Par conséquence, l’objectif de cette thèse est d’optimiser les performances du processus de découverte en utilisant des mécanismes contextuels. Dans un premier temps, nous commençons par une description préliminaire des défis auxquels sont confrontés les utilisateurs du réseau et comment les solutions actuelles (c’est-à-dire Long Term Evolution (LTE)) ne peuvent pas couvrir leurs besoins. Dans un deuxième temps, nous présentons l’architecture utilisée pour évaluer nos propositions: l’architecture appareil-à-appareil (D2D) qui est définie par le programme de partenariat de troisième génération (3GPP) pour être utilisée dans les réseaux LTE. Nous mettrons tout particulièrement l’accent sur la description du processus de découverte tel qu’il est défini dans les spécifications. Finalement, nous présentons une étude analytique, avec un modèle de mise en oeuvre pour tester et valider les performances de la découverte directe. En utilisant cette analyse, nous proposons un algorithme de transmission adaptatif qui optimise le processus de découverte pour les topologies statiques. Cette contribution sert de base à des algorithmes étendus et améliorés ciblant premièrement des scénarios où la disponibilité de données historiques permet de prédire les fluctuations de la densité des utilisateurs, et deuxièmement des situations entièrement dynamiques sans infrastructure ou support externe, montrant comment les mécanismes contextuels peuvent fournir des performances presque optimales. Toutes ces contributions et ces analyses sont supportées et validées par des modèles de simulation et des expériences qui montrent l’importance et l’exactitude de nos propositions dans l’optimisation de la performance et de la fiabilité dans le cadre de la découverte directe / Research in communication networks aims to improve the capabilities and performance of network technologies, and to satisfy the ever increasing demand for instant information access and exchange. For example, work on Fifth Generation (5G) Wireless Systems aims to increase data rates and spectral efficiency while lowering latency and energy consumption. Within this context, proximity-based networking is being considered in order to improve the data sharing between nearby devices, regardless of the availability of additional infrastructure. An integral component of these solutions is the ability to quickly detect (or discover) other systems in the vicinity. While system and service discovery has been a concept used in networks for some time, its adoption by wireless networks has increased the importance and relevance of this type of mechanisms. Therefore, the goal of this thesis is to optimize the performance of the discovery process by using context-aware mechanisms. First, we start by an introductory description of the challenges faced by network users and how current solutions (i.e. Long Term Evolution (LTE)) are unable to cover their needs. Second, we present the architecture we will use to evaluate our proposals, namely the device-to-device (D2D) architecture defined by the Third-Generation Partnership Program (3GPP) for use in LTE networks, with an emphasis on the description of the discovery process as defined in the standard specifications. Then, we present an analytical study, along with an implementation model to test and validate the performance of direct discovery. Building upon that analysis, we propose an adaptive transmission algorithm that optimizes the discovery process for static topologies. This contribution is used as the foundation for extended and enhanced algorithms targeting scenarios where the availability of historic data allows for predicting user density fluctuations, and fully dynamic situations without external infrastructure or support, showing how context-aware mechanisms can provide almost optimal performance. All these contributions and analysis are supported and validated by simulation models and experiments that showcase the importance and correctness of our proposals in the optimization of the performance and reliability in D2D direct discovery