Over recent years, wireless communication systems have been experiencing a dramatic and continuous growth in the number of subscribers, thus placing extra demands on system capacity. At the same time, keeping Quality of Service (QoS) at an acceptable level is a critical concern and a challenge to the wireless network designer. In this sense, performance analysis must be the first step in designing or improving a network. Thus, powerful mathematical tools for analysing most of the performance metrics in the network are required. A good modelling and analysis of the wireless cellular networks will lead to a high level of QoS. In this thesis, different analytical models of various handoff schemes and resource re-allocation in homogeneous and heterogeneous wireless cellular networks are developed and investigated. The sustained increase in users and the request for advanced services are some of the key motivations for considering the designing of Hierarchical Cellular Networks (HCN). In this type of system, calls can be blocked in a microcell flow over to an overlay macrocell. Microcells in the HCN can be replaced by WLANs as this can provide high bandwidth and its users have limited mobility features. Efficient sharing of resources between wireless cellular networks and WLANs will improve the capacity as well as QoS metrics. This thesis first presents an analytical model for priority handoff mechanisms, where new calls and handoff calls are captured by two different traffic arrival processes, respectively. Using this analytical model, the optimised number of channels assigned to II handover calls, with the aim of minimising the drop probability under given network scenarios, has been investigated. Also, an analytical model of a network containing two cells has been developed to measure the different performance parameters for each of the cells in the network, as well as altogether as one network system. Secondly, a new solution is proposed to manage the bandwidth and re-allocate it in a proper way to maintain the QoS for all types of calls. Thirdly, performance models for microcells and macrocells in hierarchical cellular networks have been developed by using a combination of different handoff schemes. Finally, the microcell in HCN is replaced by WLANs and a prioritised vertical handoff scheme in an integrated UMTS/WLAN network has been developed. Simulation experiments have been conducted to validate the accuracy of these analytical models. The models have then been used to investigate the performance of the networks under different scenarios.

No / Rapid advances in software systems, wireless networks, and embedded devices have led to the development of a pervasive and mobile cyberspace that provides an infrastructure for anywhere/anytime service provisioning in different domains such as engineering, commerce, education, and entertainment. This style of service provisioning enables users to freely move between geographical areas and to continuously access information and conduct online transactions. However, such a high mobility may cause performance and reliability problems during the execution of transactions. For example, the unavailability of sufficient bandwidth can result in failure of transactions when users move from one area (cell) to another. We present a context-aware transaction model that dynamically adapts to the users' needs and execution environments. Accordingly, we develop a new mobility management scheme that ensures seamless connectivity and reliable execution of context-aware transactions during mobility of users. The proposed scheme is designed and developed using a combination of different queuing models. We conduct various experiments in order to show that the proposed scheme optimizes the mobility management process and increases the throughput of context-aware transactions.

Multi-tier cellular networks have led to a paradigm shift in the deployment of base stations (BSs) where macrocell BSs are overlaid with smaller and lower power BSs such as microcells, picocells, and femtocells. Stochastic geometry has been proven to be an effective tool to capture such heterogeneity and uncertainties in deployment of cellular BSs. In stochastic geometry, random spatial models are used to model multi-tier cellular networks where the locations of BSs is each tier is assumed to be drawn from a point process with the appropriate spatial density. This thesis proposes stochastic geometry-based approaches to analyze, model, and optimize multi-tier cellular networks under several setups and technologies. First, I propose a novel location-aware cross-tier cooperation scheme that aim at improving the performance of users with low signal-to-interference-plus-noise ratio (SINR). Second, I study the performance of cognitive device-to-device (D2D) communication in multi-channel downlink-uplink cellular network with energy harvesting. For the coexistence between cellular and D2D transmissions, I propose a spectrum access policy for cellular BSs to avoid using D2D channels when possible. Third, I investigate the feasibility of energy harvesting from ambient RF interference in multi-tier uplink cellular networks. For this setup, I capture randomness in the network topology and the battery dynamics. Fourth, I extend multi-tier uplink cellular networks to consider the case when users do not necessarily associate with the nearest BS (i.e., flexible cell association). Finally, I compare between different cell association criteria including coupled and decoupled cell association for uplink and downlink transmissions in multi-tier full-duplex cellular networks. For all network setups, I use stochastic geometry to derive simple and closed-form expressions to evaluate the performance in terms of several metrics, e.g., outage probability, mean rate, transmission probability, success probability, and load per BS. I also highlight main tradeoffs in different networks and provide guidelines to optimize different performance metrics by carefully tuning fundamental network design parameters. / February 2017

The increasing complexity of heterogeneous cellular networks (HetNets) due to the irregular deployment of small cells demands significant rethinking in the way cellular networks are perceived, modeled and analyzed. In addition to threatening the relevance of classical models, this new network paradigm also raises questions regarding the feasibility of state-of-the-art simulation-based approach for system design. This dissertation proposes a fundamentally new approach based on random spatial models that is not only tractable but also captures current deployment trends fairly accurately. First, this dissertation presents a general baseline model for HetNets consisting of K different types of base stations (BSs) that may differ in terms of transmit power, deployment density and target rate. Modeling the locations of each class of BSs as an independent Poisson Point Process (PPP) allows the derivation of surprisingly simple expressions for coverage probability and average rate. One interpretation of these results is that adding more BSs or tiers does not necessarily change the coverage probability, which indicates that fears of "interference overload" in HetNets are probably overblown. Second, a flexible notion of BS load is incorporated by introducing a new idea of conditionally thinning the interference field. For this generalized model, the coverage probability is shown to increase when lightly loaded small cells are added to the existing macrocellular networks. This is due to the fact that owing to the smaller loads, small cells typically transmit less often than macrocells, thus contributing less to the interference power. The same idea of conditional thinning is also shown to be useful in modeling the non-uniform user distributions, especially when the users lie closer to the BSs. Third, the baseline model is extended to study multi-antenna HetNets, where BSs across tiers may additionally differ in terms of the number of transmit antennas, number of users served and the multi-antenna transmission strategy. Using novel tools from stochastic orders, a tractable framework is developed to compare the performance of various multi-antenna transmission strategies for a fairly general spatial model, where the BSs may follow any general stationary distribution. The analysis shows that for a given total number of transmit antennas in the network, it is preferable to spread them across many single-antenna BSs vs. fewer multi-antenna BSs. Fourth, accounting for the load on the serving BS, downlink rate distribution is derived for a generalized cell selection model, where shadowing, following any general distribution, impacts cell selection while fading does not. This generalizes the baseline model and all its extensions, which either ignore the impact of channel randomness on cell selection or lumps all the sources of randomness into a single random variable. As an application of these results, it is shown that in certain regimes, shadowing naturally balances load across various tiers and hence reduces the need for artificial cell selection bias. Fifth and last, a slightly futuristic scenario of self-powered HetNets is considered, where each BS is powered solely by a self-contained energy harvesting module that may differ across tiers in terms of the energy harvesting rate and energy storage capacity. Since a BS may not always have sufficient energy, it may not always be available to serve users. This leads to a notion of availability region, which characterizes the fraction of time each type of BS can be made available under variety of strategies. One interpretation of this result is that the self-powered BSs do not suffer performance degradation due to the unreliability associated with energy harvesting if the availability vector corresponding to the optimal system performance lies in the availability region. / text

Device-to-device (D2D) networking enables direct discovery and communication between cellular subscribers that are in proximity, thus bypassing the base stations (BSs). In principle, exploiting direct communication between nearby mobile devices will improve spectrum utilization, overall throughput, and energy consumption, while enabling new peer-to-peer and location-based applications and services. D2D-enabled broadband communication technology is also required by public safety networks that must function when cellular networks are not available. Integrating D2D into cellular networks, however, poses many challenges and risks to the long-standing cellular architecture, which is centered around the BSs. This dissertation identifies outstanding technical challenges in D2D-enabled cellular networks and addresses them with novel models and fundamental analysis. First, this dissertation develops a baseline hybrid network model consisting of both ad hoc nodes and cellular infrastructure. This model uses Poisson point processes to model the random and unpredictable locations of mobile users. It also captures key features of multicast D2D including multicast receiver heterogeneity and retransmissions while being tractable for analytical purpose. Several important multicast D2D metrics including coverage probability, mean number of covered receivers per multicast session, and multicast throughput are analytically characterized under the proposed model. Second, D2D mode selection which means that a potential D2D pair can switch between direct and cellular modes is incorporated into the hybrid network model. The extended model is applied to study spectrum sharing between cellular and D2D communications. Two spectrum sharing models, overlay and underlay, are investigated under a unified analytical framework. Analytical rate expressions are derived and applied to optimize the design of spectrum sharing. It is found that, from an overall mean-rate perspective, both overlay and underlay bring performance improvements (vs. pure cellular). Third, the single-antenna hybrid network model is extended to multi-antenna transmission to study the interplay between massive MIMO (multi-input multiple-output) and underlaid D2D networking. The spectral efficiency of such multi-antenna hybrid networks is investigated under both perfect and imperfect channel state information (CSI) assumptions. Compared to the case without D2D, there is a loss in cellular spectral efficiency due to D2D underlay. With perfect CSI, the loss can be completely overcome if the number of canceled D2D interfering signals is scaled appropriately. With imperfect CSI, in addition to pilot contamination, a new asymptotic underlay contamination effect arises. Finally, motivated by the fact that transmissions in D2D discovery are usually not or imperfectly synchronized, this dissertation studies the effect of asynchronous multicarrier transmission and proposes a tractable signal-to-interference-plus-noise ratio (SINR) model. The proposed model is used to analytically characterize system-level performance of asynchronous wireless networks. The loss from lack of synchronization is quantified, and several solutions are proposed and compared to mitigate the loss. / text

Les réseaux actuels et la prochaine génération des réseaux sans fil cellulaires (5G) doivent garantir, non seulement, les communications entre les gens (aussi connu sous le nom d'humain à humain - H2H), mais aussi à un déploiement massif de communication de type machine (MTC). MTC, ou encore Machine à Machine (M2M), peut être considérée comme des appareils qui peuvent établir des communications avec d’autres appareils sans aucune intervention humaine. M2M est aussi vue comme la pierre angulaire de la vision des objets connectés (IoT). Elle attire beaucoup d'attention, car elle peut être considérée comme une nouvelle opportunité pour les opérateurs de réseau et service IoT. Il existe aujourd’hui plusieurs types d’applications se basant sur MTC couvrant plusieurs domaines. On peut citer comme exemples les applications suivantes: la santé, les systèmes de transport intelligents (ITS), les compteurs intelligents et les réseaux intelligents, et la sécurité publique (PS). Le déploiement de ce type d'applications dans les réseaux mobiles cellulaires actuels, particulièrement Long Term Evolution (LTE) et LTE-Advanced (LTE-A) , ne peut être effectif sans surmonter les challenges posés par le déploiement d’un grand nombre d’équipement MTC dans la même cellule. En effet, le déploiement d'une myriade d'appareils MTC causera une congestion et une surcharge du système des réseaux d'accès radio (RAN) et du cœur de réseau (CN). Comme les appareils MTC sont équipés d'une batterie non rechargeable, la consommation d'énergie est aussi un défi. Dans cette thèse, nous allons étudier les problèmes de congestion et de consommation d'énergie dans le contexte des réseaux LTE et LTE-A en présence des appareils M2M. En ce qui concerne la congestion et la surcharge de système, nous nous concentrons sur la partie RAN, puisqu'elle peut être considérée comme la première ligne de défense pour le réseau cellulaire. Les contributions de cette thèse sont organisées sous les axes suivants: 1) Proposition d'un algorithme générique pour prédire le trafic entrant, de sorte que la congestion dans le réseau peut être facilement résolue, 2) Étude et proposition d'un modèle analytique générique de la procédure d'accès aléatoire au canal (RACH). Le modèle a pour but l’évaluation des méthodes de contrôle de congestion ciblant la partie RAN, 3) Approfondissement et proposition des méthodes permettant d'améliorer la méthode Pagination de Groupe (GP) approuvée par le 3GPP pour contrôler la congestion. / The current and next generation wireless cellular networks (5G) have to deal with not only communications between people (known as Human-to-Human - H2H), but also with a massive deployment of Machine-Type-Communication (MTC). MTC, or alternatively Machine-to-Machine (M2M), can be viewed as devices connected among them without any human intervention. M2M can be considered as the cornerstone of Internet-of-Things (IoT) vision. It attracts a lot of attention, since it can be considered as a new opportunity and business market. Nowadays, there is a vast number of MTC applications, covering a large number of fields. Some of these applications are Healthcare, Intelligent Transport System (ITS), smart metering and smart grids, public safety (PS), forming the so-called smart city. Deploying this type of applications in the current cellular mobile networks, especially Long Term Evolution (LTE) and LTE-Advanced (LTE-A), cannot be achieved before overcoming the accompanied challenges. Indeed, caused by the existence of a myriad of MTC devices, Radio Access Network (RAN) and Core Network (CN) congestion and system overload is one of these challenging issues. As the MTC devices are using non-rechargeable batteries, power consumption is also a challenge. In this thesis, we study the congestion and power consumption problems in the context of LTE and LTE-A networks featuring M2M communications. Regarding the congestion and system overload, the focus will be on the RAN part since it can be considered as the first defense line on the network. The contributions of the thesis are organized on the following axes: 1) Propose a general algorithm to predict the incoming traffic, so that the congestion in the network can be easily remedied, 2) Study and propose a general analytical model of the Random Access Channel (RACH) procedure. The model can help to evaluate the congestion control methods targeting the RAN part, 3) Depth study and propose methods improving the performance of Group Paging (GP) method, one of the methods approved by 3GPP to control the congestion.

L’objectif principal de cette thèse est l’analyse des performances des réseaux LTE-A (Long Term Evolution- Advanced) au travers de la géométrie stochastique. L’analyse mathématique des réseaux cellulaires est un problème difficile, pour lesquels ils existent déjà un certain nombre de résultats mais qui demande encore des efforts et des contributions sur le long terme. L’utilisation de la géométrie aléatoire et des processus ponctuels de Poisson (PPP) s’est avérée être une approche permettant une modélisation pertinente des réseaux cellulaires et d’une complexité faible (tractable). Dans cette thèse, nous nous intéressons tout particulièrement à des modèles s’appuyant sur ces processus de Poisson : PPP-based abstraction. Nous développons un cadre mathématique qui permet le calcul de quantités reflétant les performances des réseaux LTE-A, tels que la probabilité d’erreur, la probabilité et le taux de couverture, pour plusieurs scénarios couvrant entre autres le sens montant et descendant. Nous considérons également des transmissions multi-antennes, des déploiements hétérogènes, et des systèmes de commande de puissance de la liaison montante. L’ensemble de ces propositions a été validé par un grand nombre de simulations. Le cadre mathématique développé dans cette thèse se veut général, et doit pouvoir s’appliquer à un nombre d’autres scénarios importants. L’intérêt de l’approche proposée est de permettre une évaluation des performances au travers de l’évaluation des formules, et permettent en conséquences d’éviter des simulations qui peuvent prendre énormément de temps en terme de développement ou d’exécution. / The main focus of this thesis is on performance analysis and system optimization of Long Term Evolution - Advanced (LTE-A) cellular networks by using stochastic geometry. Mathematical analysis of cellular networks is a long-lasting difficult problem. Modeling the network elements as points in a Poisson Point Process (PPP) has been proven to be a tractable yet accurate approach to the performance analysis in cellular networks, by leveraging the powerful mathematical tools such as stochastic geometry. In particular, relying on the PPP-based abstraction model, this thesis develops the mathematical frameworks to the computations of important performance measures such as error probability, coverage probability and average rate in several application scenarios in both uplink and downlink of LTE-A cellular networks, for example, multi-antenna transmissions, heterogeneous deployments, uplink power control schemes, etc. The mathematical frameworks developed in this thesis are general enough and the accuracy has been validated against extensive Monte Carlo simulations. Insights on performance trends and system optimization can be done by directly evaluating the formulas to avoid the time-consuming numerical simulations.

Cette thèse porte principalement sur la modélisation, l'évaluation des performances et l'optimisation au niveau système des réseaux cellulaires de nouvelle génération à l'aide de la géométrie stochastique. En plus, la technologie émergente des surfaces intelligentes reconfigurables (RISs) est étudiée pour l'application aux futurs réseaux sans fil. En particulier, reposant sur un modèle d’abstraction basé sur la loi de Poisson pour la distribution spatiale des nœuds et des points d’accès, cette thèse développe un ensemble de nouveaux cadres analytiques pour le calcul d’importantes métriques de performance, telles que la probabilité de couverture et l'efficacité spectrale potentielle, qui peuvent être utilisés pour l'analyse et l'optimisation au niveau système. Plus spécifiquement, une nouvelle méthodologie d'analyse pour l'analyse de réseaux cellulaires tridimensionnels est introduite et utilisée pour l'optimisation du système. Un nouveau problème d’allocation de ressources est formulé et résolu en combinant pour la première fois géométrie stochastique et programmation non linéaire mixte en nombres entiers. L'impact du déploiement de surfaces réfléchissantes intelligentes sur un réseau sans fil est quantifié à l'aide de processus ponctuels, et les avantages potentiels des RISs contre le relais sont étudiés à l'aide de simulations numériques. / The main focus of this thesis is on modeling, performance evaluation and system-level optimization of next-generation cellular networks by using stochastic geometry. In addition, the emerging technology of Reconfigurable Intelligent Surfaces (RISs) is investigated for application to future wireless networks. In particular, relying on a Poisson-based abstraction model for the spatial distribution of nodes and access points, this thesis develops a set of new analytical frameworks for the computation of important performance metrics, such as the coverage probability and potential spectral efficiency, which can be used for system-level analysis and optimization. More specifically, a new analytical methodology for the analysis of three-dimensional cellular networks is introduced and employed for system optimization. A novel resource allocation problem is formulated and solved by jointly combining for the first time stochastic geometry and mixed-integer non-linear programming. The impact of deploying intelligent reflecting surfaces throughout a wireless network is quantified with the aid of line point processes, and the potential benefits of RISs against relaying are investigated with the aid of numerical simulations.

Nous vivons une révolution numérique où l’Internet est devenu un élément essentiel de notre vie quotidienne. Avec plus de 750 millions de foyers connectés et plus de 6,8 milliards d'abonnés à la téléphonie mobile, les réseaux cellulaires dominent le secteur des Technologies de l'Information et de la Communication (TIC) avec plus de 75%. La tendance est à la hausse et ne semble pas avoir de signe de ralentissement dans un avenir proche en raison des nouveaux services et applications en cours. Cependant, cette augmentation radicale des appareils et services TIC a poussé la consommation d'énergie correspondante et son impact sur l'environnement à croître à un rythme effarant, consommant plus de 5% de l'énergie électrique mondiale et libérant dans l'atmosphère environ 2% des émissions de CO2. Étant donné que les stations de base, éléments essentiels de la fourniture d’accès à l’Internet, consomment la plus grande partie de l’énergie des réseaux cellulaires, il est essentiel d’étudier de nouvelles stratégies et architectures afin de prévenir cette pénurie d’énergie. Cette thèse porte sur le rôle essentiel de l'énergie dans la conception et l'exploitation de futurs réseaux cellulaires. Nous considérons des approches différentes et complémentaires, y compris des techniques d'efficacité énergétique (gestion des ressources radio et systèmes de sommeil), des sources d'énergie renouvelables, le Smart Grid et des outils d'apprentissage basés sur l’intelligence artificiel pour réduire la consommation d'énergie de ces réseaux complexes tout en garantissant une certaine qualité de service adapté aux cas d'utilisation 5G. / We live in the digital era where the Internet has become an essential part of our daily lives. With more than 750 million connected households and over 6.8 billion mobile subscribers, mobile networks are dominating the Information and Communication Technology (ICT) sector with more than 75%. The trend is of further increase and appears to have no signs of slowing down in the near future due to the ongoing new services and applications. However, this radical surge of ICT devices and services has pushed corresponding energy consumption and its footprint on the environment to grow at a staggering rate consuming more than 5% of the world’s electrical energy and releasing into the atmosphere about 2% of the global CO2 emissions. Since base stations, the core elements to provide internet access, consume most of the energy in cellular networks, it is essential to study new strategies and architectures in order to deter this energy crunch. This thesis focuses on the crucial role of energy in the design and operation of future cellular networks. We consider different and complementary approaches and parameters, including energy efficiency techniques (i.e., radio resource management and sleep schemes), renewable energy sources, Smart Grid and tools from machine learning to bring down the energy consumption of these complex networks while guaranteeing a certain quality of service adapted to 5G use cases.

New developments in web transport such as HTTP/2 and first and foremost QUIC promise fewer connections to track as well as shorter connection setup times. These protocols have proven themselves on modern reliable connections with a high bandwidth-delay-product, but how do they perform over cellular connections in rural or crowded areas where the connections are much more unreliable? A lot of new users of the web in todays mobile-first usage scenarios are located on poor connections. A testbench was designed that allowed for web browsing over limited network links in a con- trolled environment. We have compared the network load time of page loading over the protocols QUIC, HTTP/2 and HTTP/1.1 using a variety of different network conditions. We then used these measurements as a basis for suggesting which protocol to use during different conditions. The results show that newer is not always better. QUIC in general works reasonably well under all conditions, while HTTP/1.1 and HTTP/2 trade blows depending on connection conditions, with HTTP/1.1 sometimes outperforming both of the newer protocols.