Face à la demande croissante de débits de données de plus en plus élevées, l’une des principales solutions proposées par la 5G est de densifier le réseau en y intégrant notamment de nouvelles « Small cells ». La réorganisation de l’architecture du réseau mobile pour s’adapter à l’intégration poussée de ces Small cells, fait naître la problématique de la connexion backhaul entre les stations de bases desservant les Small cells et le cœur de réseau. Ainsi, des liaisons backhaul de plusieurs Gb/s de données sont nécessaires pour pouvoir assurer un débit de données d’au moins 100Mb/s à l’utilisateur qui est l’un des objectifs fixés pour la 5G. Les solutions de connexion backhaul sans fils ont un avantage indiscutable face aux coûts de déploiements de fibres optiques qui sont très élevés. Pour augmenter la capacité spectrale des liaisons sans fils, l’utilisation des fréquences millimétriques au-delà de 6 GHz caractérisées par des larges bandes passantes sera prochainement discutée pour la 5G durant le World Radiocommunication Conference 2019. Parmi ces fréquences, les bandes V (57-66GHz) et E (71-76 GHz et 81-86 GHz) ont un intérêt indéniable grâce aux larges bandes passantes disponibles ainsi qu’aux conditions de licenciement peu exigeantes. Les travaux développés dans cette thèse consistent à concevoir des antennes directives à large bande passante permettant d’établir les liens backhaul point-à-point sans fils (LoS). En exploitant les technologies de fabrications à faibles coût telles que l’impression 3D et Printed Circuit Board (PCB) sur des substrats FR4, la conception de deux types d’antenne directives a été étudiée à savoir des antennes lentilles et des antennes réseaux. / In order to address the ever-increasing demand of higher data rates, adding small cells to the existing macrocells infrastructure is one of the most important milestones of the 5G roadmap. With the integration of small cells and the re-organization of the network topology, backhaul bottleneck is the main challenge to address in the near future. Facing the costs of deployments of fiber optic connections, point-to-point wireless backhaul links using millimeter wave (mmW) frequencies are gaining prominence. 5G future frequencies, to be discussed under the World Radiocommunication Conference 2019 (WRC-19) open-up the way towards mmW frequency band where large bandwidths are naturally available. The high bandwidths available at these frequencies enable several Gbps data rate backhaul links, which is un utmost necessity to respect the 100 Mbps user-experienced data rate promised by the 5G standard. Millimeter-wave frequencies in V and E-bands unlicensed/light licensed spectrum are considered as primary candidates for backhaul links. In addition to the light license regime, the high free space path loss experienced at these frequencies is rather beneficial to limit the interference between small cells links. Moreover, the high available bandwidths at V and E-bands enable to achieve multi Gb/s links without using complex modulation schemes. In this thesis, we focused our research study on developing high gain wide-band antennas usable in point-to-point backhaul links in a Line of Sight (LoS) context. Leveraging cost-efficient technologies like 3D printing and Printed Circuit Board (PCB) on FR4 substrates, we studied two high-gain antenna types: lens antennas and flat array antennas.

Mobile data traffic is expected to increase substantially in the coming years, with data rates 1000 times higher by 2020, having media and content as the main drivers together with a plethora of new end-user services that will challenge existing networks. Concepts and visions associated with the ICT evolution like the network society, 50 billion connected devices, Industrial Internet, Tactile Internet, etc., exemplifies the range of new services that the networks will have to handle. These new services impose extreme requirement to the network like high capacity, low latency, reliability, security, seamless connectivity, etc. In order to face these challenges, the whole end-to-end network has to evolve and adapt, pushing for advances in different areas, such as transport, cloud, core, and radio access networks. This work investigates the impact of envisioned 2020 society scenarios on transport links for mobile backhaul, emphasizing the need for an integrated and flexible/adaptive network as the way to meet the 2020 networks demands. The evolution of heterogeneous networks and ultra-dense network deployments shall also comprise the introduction of adaptive network features, such as dynamic network resource allocation, automatic integration of access nodes, etc. In order to achieve such self-management features in mobile networks, new mechanisms have to be investigated for an integrated backhaul management. First, this thesis performs a feasibility study on the mobile backhaul dimensioning for 2020 5G wireless ultra-dense networks scenarios, aiming to analyze the gap in capacity demand between 4G and 5G networks. Secondly, the concept of an integrated backhaul management is analyzed as a combination of node attachment procedures, in the context of moving networks. In addition, the dynamic network resource allocation concept, based on DWDM-centric transport architecture, was explored for 5G scenarios assuming traffic variation both in time and between different geographical areas. Finally, a short view on techno-economics and network deployments in the 2020 time frame is provided.

La coopération des émetteurs est considérée comme une approche prometteuse pour limiter les interférences dans les réseaux sans fil ayant une réutilisation des ressources spectrales très agressive. La coopération des émetteurs permet l'optimisation conjointe de certains paramètres de transmission. Bien que la coopération des émetteurs existe sous différentes formes, une hypothèse commune est le besoin pour les émetteurs entrant en coopération (i) d’acquérir et de partager des informations concernant le canal de propagation ainsi que (ii) d’effectuer une coopération fondée sur les informations diffusées à l'étape précédente. La conception coordonnée des matrices de précodage et, d’une manière encore plus marquée, la transmission conjointe à différents émetteurs sont des exemples importants de méthodes de coopérations présentant ces propriétés. L’acquisition et l'échange de l’information de canal étant strictement limités, il se pose deux questions importantes: (i) Quelle information doit être renvoyée ou échangée de manière à permettre la coopération la plus efficace? (ii) Quelles méthodes permettent de réaliser les gains de la coopération dans ce contexte de partage limité et imparfait d’information? Dans cette thèse, nous abordons les deux questions précédentes. Dans un premier temps, nous considérons que chaque émetteur acquiert une estimée de canal imparfaite. Dans un second temps, nous étudions la conception de techniques de coopération efficaces dans une configuration d’information de canal imparfaitement partagée entre les émetteurs. Enfin, les futures directions de recherche découlant de ces travaux sont présentées et discutées. / Transmitter cooperation is considered a promising tool for dealing with interference in wireless networks with an aggressive reuse policy of spectral resources. Although transmitter cooperation comes in many flavors, a recurrent assumption behind proposed methods lies in the need for cooperating devices to (i) acquire, share information pertaining to the propagation channel toward the multiple receivers and (ii) perform cooperation based on the disseminated information in the previous step. This holds true for instance for coordinated beamforming methods and, to an even greater extent, for network-MIMO (Joint Processing coordinated multi-point (JP CoMP) in the long term evolution (LTE) terminology). As feedback and exchange of channel state information (CSI) come at a price in terms of signaling overhead, there arise two important questions: (i) What information should be fed back or exchanged such that the CSI acquired at each transmitter is most informative to perform cooperation? (ii) Which techniques can reap the benefits of cooperation while living with an imperfect channel representation that varies from transmitter to transmitter ? In this thesis, we address both aforementioned questions. We consider first each transmitter acquires an initial imperfect CSI based on limited receivers feedback. For the design of efficient cooperation techniques that copes with the imperfect and non-identical CSI configuration at each transmitter, we investigate specifically a regularized zero forcing (RZF) precoder design in large system scenario. Finally, interesting and challenging research directions and open problems are discussed.

Les avancées technologiques poussent l'industrie des télécommunications à fournir la capacité et la qualité nécessaire pour satisfaire la demande croissante de services sans fil à haut débit. De plus, avec les progrès des technologies d'accès, le goulot d'étranglement des réseaux cellulaires se déplace progressivement de l'interface radio vers le backhaul -- la partie de l'infrastructure du réseau qui fournit l'interconnexion entre les réseaux d'accès et de coeur. Aussi, la possibilité de déployer rapidement des liens radio micro-ondes efficaces est essentielle pour apporter des solutions crédibles au problème de l'engorgement des réseaux backhaul. Toutefois, les solutions de backhaul disponibles avec cette technologie ont reçu peu d'attention de la communauté scientifique. Pourtant, la croissance des réseaux backhaul et l'augmentation de leur complexité posent de nombreux problèmes d'optimisation très intéressants. En effet, contrairement aux réseaux filaires, la capacité d'un lien radio micro-ondes est sujette à variation, soit due à des facteurs extérieurs (météo), soit par l'action de l'opérateur. Cette différence fondamentale soulève une variété de nouvelles questions qui doivent être abordées de façon appropriée. Il faut donc concevoir des méthodes adéquates pour l'optimisation des réseaux backhaul. Dans cette thèse, nous étudions les problèmes d'optimisation de réseaux liés à la conception et la configuration des liaisons terrestres sans fil à micro-ondes. Nous nous intéressons en particulier à la classe des problèmes de multiflot de coût minimum avec des fonctions de coût en escalier sur les liens du réseau. Ces problèmes sont parmi les problèmes d'optimisation combinatoire les plus importants et les plus difficiles dans l'optimisation des réseaux, et il n'est généralement possible de les résoudre que de façon approchée. Nous introduisons des modèles mathématiques pour certains de ces problèmes et présentons des approches de solution basées essentiellement sur la programmation entière mixte, la programmation sous contraintes probabilistes, des techniques de relaxation, des méthodes de coupe, ainsi que des méta-heuristiques hybrides. Ces travaux ont été effectués en collaboration avec la PME~3Roam, et partiellement dans le cadre du projet RAISOM (Réseaux de Collecte IP sans fil optimisés) entre le projet Mascotte et les PMEs 3Roam et Avisto. Cette thèse a été développée en co-tutelle entre l'Université de Nice-Sophia Antipolis et l'Université Federale du Ceará.

La interfaz radio de los sistemas de comunicaciones móviles es normalmente considerada como la única limitación de capacidad en la red de acceso radio. Sin embargo, a medida que se van desplegando nuevas y más eficientes interfaces radio, y de que el tráfico de datos y multimedia va en aumento, existe la creciente preocupación de que la infraestructura de transporte (backhaul) de la red celular pueda convertirse en el cuello de botella en algunos escenarios. En este contexto, la tesis se centra en el desarrollo de técnicas de gestión de recursos que consideran de manera conjunta la gestión de recursos en la interfaz radio y el backhaul. Esto conduce a un nuevo paradigma donde los recursos del backhaul se consideran no sólo en la etapa de dimensionamiento, sino que además son incluidos en la problemática de gestión de recursos. Sobre esta base, el primer objetivo de la tesis consiste en evaluar los requerimientos de capacidad en las redes de acceso radio que usan IP como tecnología de transporte, de acuerdo a las recientes tendencias de la arquitectura de red. En particular, se analiza el impacto que tiene una solución de transporte basada en IP sobre la capacidad de transporte necesaria para satisfacer los requisitos de calidad de servicio en la red de acceso. La evaluación se realiza en el contexto de la red de acceso radio de UMTS, donde se proporciona una caracterización detallada de la interfaz Iub. El análisis de requerimientos de capacidad se lleva a cabo para dos diferentes escenarios: canales dedicados y canales de alta velocidad. Posteriormente, con el objetivo de aprovechar totalmente los recursos disponibles en el acceso radio y el backhaul, esta tesis propone un marco de gestión conjunta de recursos donde la idea principal consiste en incorporar las métricas de la red de transporte dentro del problema de gestión de recursos. A fin de evaluar los beneficios del marco de gestión de recursos propuesto, esta tesis se centra en la evaluación del problema de asignación de base, como estrategia para distribuir el tráfico entre las estaciones base en función de los niveles de carga tanto en la interfaz radio como en el backhaul. Este problema se analiza inicialmente considerando una red de acceso radio genérica, mediante la definición de un modelo analítico basado en cadenas de Markov. Dicho modelo permite calcular la ganancia de capacidad que puede alcanzar la estrategia de asignación de base propuesta. Posteriormente, el análisis de la estrategia propuesta se extiende considerando tecnologías específicas de acceso radio. En particular, en el contexto de redes WCDMA se desarrolla un algoritmo de asignación de base basado en simulatedannealing cuyo objetivo es maximizar una función de utilidad que refleja el grado de satisfacción de las asignaciones respecto los recursos radio y transporte. Finalmente, esta tesis aborda el diseño y evaluación de un algoritmo de asignación de base para los futuros sistemas de banda ancha basados en OFDMA. En este caso, el problema de asignación de base se modela como un problema de optimización mediante el uso de un marco de funciones de utilidad y funciones de coste de recursos. El problema planteado, que considera que existen restricciones de recursos tanto en la interfaz radio como en el backhaul, es mapeado a un problema de optimización conocido como Multiple-Choice Multidimensional Knapsack Problem (MMKP). Posteriormente, se desarrolla un algoritmo de asignación de base heurístico, el cual es evaluado y comparado con esquemas de asignación basados exclusivamente en criterios radio. El algoritmo concebido se basa en el uso de los multiplicadores de Lagrange y está diseñado para aprovechar de manera simultánea el balanceo de carga en la intefaz radio y el backhaul.

Wireless access networks today consume 0.5 percent of the global energy. Rapidly growing demand for new services and ubiqutious connectivity, will further increase the energy consumption. This situation imposes a big challenge for mobile operators not only due to soaring cost of energy, but also increasing concern for global warming and sustainable development. This thesis focuses on the energy efficiency issue at the system level and studies how to incorporate energy-awareness into the design of future wireless access networks. The main contributions have been given in the areas of energy efficiency assessment, architectural and operational solutions, and total cost of investment analysis. The precise evaluation of energy efficiency is the first essential step to determine optimized solutions where metrics and models constitute the two key elements.We show that maximizing energy efficiency is not always equivalent to minimizing energy consumption which is one of the main reasons behind the presented contradictory and disputable conclusions in the literature. Further we indicate that in order to avoid the debatable directions, energy efficient network design problems should be formulated with well defined coverage and capacity requirements. Moreover, we propose novel backhaul power consumption models considering various technology and architectural options relevant for urban and rural environments and show that backhaul will potentially become a bottleneck in future ultra-high capacity wireless access networks. Second, we focus on clean-slate network deployment solutions satisfying different quality of service requirements in a more energy efficient manner. We identify that the ratio between idle- and transmit power dependent power consumption of a base station as well as the network capacity requirement are the two key parameters that affect the energy-optimum design.While results show that macro cellular systems are the most energy efficient solution for moderate average traffic density, Hetnet solutions prevail homogeneous deployment due to their ability to increase the capacity with a relatively lower energy consumption and thus enable significant energy savings in medium and high capacity demand regions. Moreover, we investigate the energy saving potential of short-term energy aware management approach, i.e., cell DTX, taking advantage of low resource utilization in the current networks arising from strict QoS requirements. With the help of developed novel quantitative method, we show that Cell DTX brings striking reduction in energy consumption and further savings are achievable if the networks are designed taking into account the fact that network deployment and operation are closely related. Finally, we develop a general framework for investigating the main cost elements and for evaluating the viability of energy efficient solutions.We first reveal the strong positive impact of spectrum on both energy and infrastructure cost and further indicate that applying sustainable solutions might also bring total cost reduction, but the viability highly depends on unit cost values as well as the indirect cost benefits of energy efficiency. Results obtained in this dissertation might provide guidelines for the network designers to achieve future high-capacity and sustainable wireless access networks. / <p>QC 20140505</p>

Current technological advances have caused an exponential growth of the number of mobile Internet-connected devices, along with their respective traffic demands. To cope with this increase of traffic demands, fifth generation (5G) network architectures will need to provide multi-gigabit capacity at the access base stations (BSs), through the deployment of ultra-dense small cells (SCs) operating with millimeter-wave (mmWave) frequencies, e.g. 60 GHz. To connect the BSs to the core network, a robust and high capacity backhaul infrastructure is required. As it is unfeasible to connect all the SCs through optical fiber links, a solution for the future 5G backhaul relies on the usage of mmWave frequencies to interconnect the SCs, forming multi-hop wireless mesh topologies. In this thesis, we explore the application of the Software-defined Networking (SDN) paradigm for the management of a SC wireless backhaul. With SDN, the data and control planes are separated and the network management is done by a centralized controller entity that has a global network view. To that end, we provide multiple contributions. Firstly, we provide an SDN-based architecture to manage SC backhaul networks, which include an out-of-band Long Term Evolution (LTE) control channel and where we consider aspects such as energy efficiency, resiliency and flexible backhaul operation. Secondly, we demonstrate the benefit of the wireless backhaul configuration using the SDN controller, which can be used to improve the wireless resource allocation and provide resiliency mechanisms in the network. Finally, we investigate how a SC mesh backhaul can be optimally reconfigured between different topologies, focusing on minimizing the network disruption during the reconfiguration. / The growth of mobile devices, along with their traffic demands, is expected to saturate the current mobile networks soon. To cope with such demand increase, fifth generation (5G) network architectures will need to provide multi-gigabit capacity at the access level, through the deployment of a massive amount of ultra-dense small cells (SCs). To connect the access and core networks, a robust and high capacity backhaul is required. To that end, mmWave links that operate at e.g. 60 GHz, can be used to interconnect the SCs, forming multi-hop wireless mesh topologies.   In this thesis, we study the application of the Software-defined Networking (SDN) paradigm for the management of a SC wireless backhaul. Firstly, we provide an SDN-based architecture to manage SC backhaul networks, which includes an out-of-band control channel and where we consider aspects such as energy efficiency, resiliency and flexible backhaul operation. Secondly, we show the benefits of the wireless backhaul configuration using the SDN controller, which can be used to improve the wireless resource allocation and provide network resiliency. Finally, we investigate how a SC mesh backhaul can be optimally reconfigured between different topologies, while minimizing the network disruption during the reconfiguration.

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.

Fixed wireless communication is a cost-efficient solution for flexible and rapid front-/backhaul deployments. Technologies including dual polarization, carrier aggregation, and higher order modulation schemes have been developed for enhancing its throughput. In order to better support the massive traffic increment during network evolution, novel wireless backhaul solutions with possible new dimensions in increasing the spectral efficiency are needed. Line-of-Sight (LoS) Multiple-Input-Multiple-Output (MIMO) communication is such a promising candidate allowing the throughput to scale linearly with the deployed antenna pairs. Spatial multiplexing with sub-channels having approximately equal quality exists within a single LoS direction. In addition, operating at millimeter wave (mmWave) frequencies or higher, the abundantly available bandwidth can further enhance the throughput of LoS MIMO communication. The mmWave LoS MIMO communication in this work exploits the spatial multiplexing from the structured phase couplings of a single path direction, while most of the state-of-the-art works in mmWave communication focus on the spatial multiplexing from the spatial signature of multiple path directions. Challenges: The performance of a LoS MIMO system is highly dependent on the antenna topology. Topologies resulting in theoretically orthogonal channels are considered as optimal arrangements. The general topology solution from a unified viewpoint is unknown. The known optimal arrangements in the literature are rather independently derived and contain restrictions on their array planes. Moreover, operating at mmWave frequencies with wideband signals introduces additional challenges. On one hand, high pathloss is one limiting factor of the received signal power. On the other hand, high symbol rates and relatively high antenna numbers create challenges in signal processing, especially the required complexity for compensating hardware imperfections and applying beamforming. Targets: In this thesis, we focus on antenna topologies and signal processing schemes to effectively handle the complexity challenge in LoS MIMO communications. Considering the antenna topology, we target a general solution of optimal arrangements on any arbitrarily curved surface. Moreover, we study the antenna topologies with which the system gains more streams and better received signals. Considering the signal processing, we look for low complexity schemes that can effectively compensate the hardware impairments and can cope with a large number of antennas. Main Contributions: The following models and algorithms are developed for understanding mmWave LoS spatial multiplexing and turning it into practice. First, after analyzing the relation between the phase couplings and the antenna positions in three dimensional space, we derive a channel factorization model for LoS MIMO communication. Based on this, we provide a general topology solution from a projection point of view and show that the resulting spatial multiplexing is robust against moderate displacement errors. In addition, we propose a multi-subarray LoS MIMO system for jointly harvesting the spatial multiplexing and array gains. Then, we propose a novel algorithm for LoS MIMO channel equalization, which is carried out in the reverse order w.r.t. the channel factorization model. The number of multiplications in both digital and analog implementations of the proposed solution is found to increase approximately linearly w.r.t. the number of antennas. The proposed algorithm thus potentially reduces complexity for equalizing the channel during the system expansion with more streams. After this, we focus on algorithms that can effectively estimate and compensate the hardware impairments. A systolic/pipelined processing architecture is proposed in this work to achieve a balance between computational complexity and performance. The proposed architecture is a viable approach that scales well with the number of MIMO streams. With the recorded data from a hardware-in-the-loop demonstrator, it is shown that the proposed algorithms can provide reliable signal estimates at a relatively low complexity level. Finally, a channel model is derived for mmWave systems with multiple widely spaced subarrays and multiple paths. The spatial multiplexing gain from the spatial signature of multiple path directions and the spatial multiplexing gain from the structured phase couplings of a single path direction are found simultaneously at two different levels of the antenna arrangements. Attempting to exploit them jointly, we propose to use an advanced hybrid analog/digital beamforming architecture to efficiently process the signals at reasonable costs and complexity. The proposed system can overcome the low rank property caused by the limited number of propagation paths.

The mathematical modeling and performance analysis of cellular networks have seen a major paradigm shift with the application of stochastic geometry. The main purpose of stochastic geometry is to endow probability distributions on the locations of the base stations (BSs) and users in a network, which, in turn, provides an analytical handle on the performance evaluation of cellular networks. To preserve the tractability of analysis, the common practice is to assume complete spatial randomness} of the network topology. In other words, the locations of users and BSs are modeled as independent homogeneous Poisson point processes (PPPs). Despite its usefulness, the PPP-based network models fail to capture any spatial coupling between the users and BSs which is dominant in a multi-tier cellular network (also known as the heterogeneous cellular networks (HetNets)) consisting of macro and small cells. For instance, the users tend to form hotspots or clusters at certain locations and the small cell BSs (SBSs) are deployed at higher densities at these locations of the hotspots in order to cater to the high data demand. Such user-centric deployments naturally couple the locations of the users and SBSs. On the other hand, these spatial couplings are at the heart of the spatial models used in industry for the system-level simulations and standardization purposes. This dissertation proposes fundamentally new spatial models based on stochastic geometry which closely emulate these spatial couplings and are conductive for a more realistic and fine-tuned performance analysis, optimization, and design of cellular networks. First, this dissertation proposes a new class of spatial models for HetNets where the locations of the BSs and users are assumed to be distributed as Poisson cluster process (PCP). From the modeling perspective, the proposed models can capture different spatial couplings in a network topology such as the user hotspots and user BS coupling occurring due to the user-centric deployment of the SBSs. The PCP-based model is a generalization of the state-of-the-art PPP-based HetNet model. This is because the model reduces to the PPP-based model once all spatial couplings in the network are ignored. From the stochastic geometry perspective, we have made contributions in deriving the fundamental distribution properties of PCP, such as the distance distributions and sum-product functionals, which are instrumental for the performance characterization of the HetNets, such as coverage and rate. The focus on more refined spatial models for small cells and users brings to the second direction of the dissertation, which is modeling and analysis of HetNets with millimeter wave (mm-wave) integrated access and backhaul (IAB), an emerging design concept of the fifth generation (5G) cellular networks. While the concepts of network densification with small cells have emerged in the fourth generation (4G) era, the small cells can be realistically deployed with IAB since it solves the problem of high capacity wired backhaul of SBSs by replacing the last-mile fibers with mm-wave links. We have proposed new stochastic geometry-based models for the performance analysis of IAB-enabled HetNets. Our analysis reveals some interesting system-design insights: (1) the IAB HetNets can support a maximum number of users beyond which the data rate drops below the rate of a single-tier macro-only network, and (2) there exists a saturation point of SBS density beyond which no rate gain is observed with the addition of more SBSs. The third and final direction of this dissertation is the combination of machine learning and stochastic geometry to construct a new class of data driven network models which can be used in the performance optimization and design of a network. As a concrete example, we investigate the classical problem of wireless link scheduling where the objective is to choose an optimal subset of simultaneously active transmitters (Tx-s) from a ground set of Tx-s which will maximize the network-wide sum-rate. Since the optimization problem is NP-hard, we replace the computationally expensive heuristic by inferring the point patterns of the active Tx-s in the optimal subset after training a determinantal point process (DPP). Our investigations demonstrate that the DPP is able to learn the spatial interactions of the Tx-s in the optimal subset and gives a reasonably accurate estimate of the optimal subset for any new ground set of Tx-s. / Doctor of Philosophy / The high speed global cellular communication network is one of the most important technologies, and it continues to evolve rapidly with every new generation. This evolution greatly depends on observing performance-trends of the emerging technologies on the network models through extensive system-level simulations. Since these simulation models are extremely time-consuming and error prone, the complementary analytical models of cellular networks have been an area of active research for a long time. These analytical models are intended to provide crisp insights on the network behavior such as the dependence of network performance metrics (such as coverage or rate) on key system-level parameters (such as transmission powers, base station (BS) density) which serve as the prior knowledge for more fine-tuned simulations. Over the last decade, the analytical modeling of the cellular networks has been driven by stochastic geometry. The main purpose of stochastic geometry is to endow the locations of the base stations (BSs) and users with probability distributions and then leverage the properties of these distributions to average out the spatial randomness. This process of spatial averaging allows us to derive the analytical expressions of the system-level performance metrics despite the presence of a large number of random variables (such as BS and user locations, channel gains) under some reasonable assumptions. The simplest stochastic geometry based model of cellular networks, which is also the most tractable, is the so-called Poisson point process (PPP) based network model. In this model, users and BSs are assumed to be distributed as independent homogeneous PPPs. This is equivalent to saying that the users and BSs independently and uniformly at random over a plane. The PPP-based model turned out to be a reasonably accurate representation of the yesteryear’s cellular networks which consisted of a single tier of macro BSs (MBSs) intended to provide a uniform coverage blanket over the region. However, as the data-hungry devices like smart-phones, tablets, and application like online gaming continue to flood the consumer market, the network configuration is rapidly deviating from this baseline setup with different spatial interactions between BSs and users (also termed spatial coupling) becoming dominant. For instance, the user locations are far from being homogeneous as they are concentrated in specific areas like residential and commercial zones (also known as hotspots). Further, the network, previously consisting of a single tier of macro BSs (MBSs), is becoming increasingly heterogeneous with the deployment of small cell BSs (SBSs) with small coverage footprints and targeted to serve the user hotspots. It is not difficult to see that the network topology with these spatial couplings is quite far from complete spatial randomness which is the basis of the PPP-based models. The key contribution of this dissertation is to enrich the stochastic geometry-based mathematical models so that they can capture the fine-grained spatial couplings between the BSs and users. More specifically, this dissertation contributes in the following three research directions. Direction-I: Modeling Spatial Clustering. We model the locations of users and SBSs forming hotspots as Poisson cluster processes (PCPs). A PCP is a collection of offspring points which are located around the parent points which belong to a PPP. The coupling between the locations of users and SBSs (due to their user-centric deployment) can be introduced by assuming that the user and SBS PCPs share the same parent PPP. The key contribution in this direction is the construction of a general HetNet model with a mixture of PPP and PCP-distributed BSs and user distributions. Note that the baseline PPP-based HetNet model appears as one of the many configurations supported by this general model. For this general model, we derive the analytical expressions of the performance metrics like coverage probability, BS load, and rate as functions of the coupling parameters (e.g. BS and user cluster size). Direction-II: Modeling Coupling in Wireless Backhaul Networks. While the deployment of SBSs clearly enhances the network performance in terms of coverage, one might wonder: how long network densification with tens of thousands of SBSs can meet the everincreasing data demand? It turns out that in the current network setting, where the backhaul links (i.e. the links between the BSs and core network) are still wired, it is not feasible to densify the network beyond some limit. This backhaul bottleneck can be overcome if the backhaul links also become wireless and the backhaul and access links (link between user and BS) are jointly managed by an integrated access and backhaul (IAB) network. In this direction, we develop the analytical models of IAB-enabled HetNets where the key challenge is to tackle new types of couplings which exist between the rates on the wireless access and backhaul links. Such couplings exist due to the spatial correlation of the signal qualities of the two links and the number of users served by different BSs. Two fundamental insights obtained from this work are as follows: (1) the IAB HetNets can support a maximum number of users beyond which the network performance drops below that of a single-tier macro-only network, and (2) there exists a saturation point of SBS density beyond which no performance gain is observed with the addition of more SBSs. Direction-III: Modeling Repulsion. In this direction, we focus on modeling another aspect of spatial coupling imposed by the intra-point repulsion. Consider a device-to-device (D2D) communication scenario, where some users are transmitting some on-demand content locally cached in their devices using a common channel. Any reasonable multiple access scheme will ensure that two nearly users are never simultaneously active as they will cause severe mutual interference and thereby reducing the network-wide sum rate. Thus the active users in the network will have some spatial repulsion. The locations of these users can be modeled as determinantal point processes (DPPs). The key property of DPP is that it forms a bridge between stochastic geometry and machine learning, two otherwise non-overlapping paradigms for wireless network modeling and design. The main focus in this direction is to explore the learning framework of DPP and bring together advantages of stochastic geometry and machine learning to construct a new class of data-driven analytical network models.