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Next-generation cellular systems will rely on millimeter wave (mmWave) bands to meet the increasing demand for wireless connectivity from end user equipment. Given large available bandwidth and small-sized antenna elements, mmWave frequencies can support high communication rates and facilitate the use of multiple-input-multiple-output (MIMO) techniques to increase the wireless capacity. However, the small wavelength of mmWave yields severe path loss and high channel uncertainty. Meanwhile, using a large number of antenna elements requires a high energy consumption and heavy communication overhead for MIMO transmissions and channel measurement. To facilitate efficient mmWave communications, in this dissertation, the challenges of energy efficiency and communication overhead are addressed. First, the use of unmanned aerial vehicle (UAV), intelligent signal reflector, and device-to-device (D2D) communications are investigated to improve the reliability and energy efficiency of mmWave communications in face of blockage. Next, to reduce the communication overhead, new channel modeling and user localization approaches are developed to facilitate MIMO channel estimation by providing prior knowledge of mmWave links. Using advance mathematical tools from machine learning (ML), game theory, and communication theory, this dissertation develops a suite of novel frameworks using which mmWave communication networks can be reliably deployed and operated in wireless cellular systems, UAV networks, and wearable device networks. For UAV-based wireless communications, a learning framework is developed to predict the cellular data traffic during congestion events, and a new framework for the on-demand deployment of UAVs is proposed to offload the excessive traffic from the ground base stations (BSs) to the UAVs. The results show that the proposed approach enables a dynamical and optimal deployment of UAVs that alleviates the cellular traffic congestion. Subsequently, a novel energy-efficient framework is developed to reflect mmWave signals from a BS towards mobile users using a UAV-carried intelligent reflector (IR). To optimize the location and reflection coefficient of the UAV-carried IR, a deep reinforcement learning (RL) approach is proposed to maximize the downlink transmission capacity. The results show that the RL-based approach significantly improves the downlink line-of-sight probability and increases the achievable data rate. Moreover, the channel estimation challenge for MIMO communications is addressed using a distributional RL approach, while optimizing an IR-aided downlink multi-user communication. The results show that the proposed method captures the statistic feature of MIMO channels, and significantly increases the downlink sum-rate. Moreover, in order to capture the characteristics of air-to-ground channels, a data-driven approach is developed, based on a distributed framework of generative adversarial networks, so that each UAV collects and shares mmWave channel state information (CSI) for cooperative channel modeling. The results show that the proposed algorithm enables an accurate channel modeling for mmWave MIMO communications over a large temporal-spatial domain. Furthermore, the CSI pattern is analyzed via semi-supervised ML tools to localize the wireless devices in the mmWave networks. Finally, to support D2D communications, a novel framework for mmWave multi-hop transmissions is investigated to improve the performance of the high-rate low-latency transmissions between wearable devices. In a nutshell, this dissertation provides analytical foundations on the ML-based performance optimization of mmWave communication systems, and the anticipated results provide rigorous guidelines for effective deployment of mmWave frequency bands into next-generation wireless systems (e.g., 6G). / Doctor of Philosophy / Different kinds of new smart devices are invented and deployed every year. Emerging smart city applications, including autonomous vehicles, virtual reality, drones, and Internet-of-things, will require the wireless communication system to support more data transmissions and connectivity. However, existing wireless network (e.g., 5G and Wi-Fi) operates at congested microwave frequency bands and cannot satisfy needs of these applications due to limited resources. Therefore, a different, very high frequency band at the millimeter wave (mmWave) spectrum becomes an inevitable choice to manage the exponential growth in wireless traffic for next-generation communication systems. With abundant bandwidth resources, mmWave frequencies can provide the high transmission rate and support the wireless connectivity for the massive number of devices in a smart city. Despite the advantages of communications at the mmWave bands, it is necessary to address the challenges related to high-frequency transmissions, such as low energy efficiency and unpredictable link states. To this end, this dissertation develops a set of novel network frameworks to facilitate the service deployment, performance analysis, and network optimization for mmWave communications. In particular, the proposed frameworks and efficient algorithms are tailored to the characteristics of mmWave propagation and satisfy the communication requirements of emerging smart city applications. Using advanced mathematical tools from machine learning, game theory, and wireless communications, this dissertation provides a comprehensive understanding of the communication performance over mmWave frequencies in the cellular systems, wireless local area networks, and drone networks. The anticipated results will promote the deployment of mmWave frequencies in next-generation communication systems.

Emerging wireless networks are foreseen as an integration of heterogeneous spectrum bands, wireless access technologies, and backhaul solutions, as well as a large-scale interconnection of devices, people, and vehicles. Such a heterogeneity will range from the proliferation of multi-tasking user devices with different capabilities such as smartphones and tablets to the deployment of multi-mode access points that can operate over heterogeneous frequency bands spanning both sub-6 GHz microwave and high-frequency millimeter wave (mmW) frequencies bands. This heterogeneous ecosystem will yield new challenges and opportunities for wireless resource management. On the one hand, resource management can exploit user and network-specific context information, such as application type, social metrics, or operator pricing, to develop application-driven, context-aware networks. Similarly, multiple frequency bands can be leveraged to meet the stringent and heterogeneous quality-of-service (QoS) requirements of the new wireless services such as video streaming and interactive gaming. On the other hand, resource management in such heterogeneous, multi-band, and large-scale wireless systems requires distributed frameworks that can effectively utilize all available resources while operating with manageable overhead. The key goal of this dissertation is therefore to develop novel, self-organizing, and low-complexity resource management protocols -- using techniques from matching theory, optimization, and machine learning -- to address critical resource allocation problems for emerging heterogeneous wireless systems while explicitly modeling and factoring diverse network context information. Towards achieving this goal, this dissertation makes a number of key contributions. First, a novel context-aware scheduling framework is developed for enabling dual-mode base stations to efficiently and jointly utilize mmW and microwave frequency resources while maximizing the number of user applications whose stringent delay requirements are satisfied. The results show that the proposed approach will be able to significantly improve the QoS per application and decrease the outage probability. Second, novel solutions are proposed to address both network formation and resource allocation problems in multi-hop wireless backhaul networks that operate at mmW frequencies. The proposed framework motivates collaboration among multiple network operators by resource sharing to reduce the cost of backhauling, while jointly accounting for both wireless channel characteristics and economic factors. Third, a novel framework is proposed to exploit high-capacity mmW communications and device-level caching to minimize handover failures as well as energy consumption by inter-frequency measurements, and to provide seamless mobility in dense heterogeneous mmW-microwave small cell networks (SCNs). Fourth, a new cell association algorithm is proposed, based on matching theory with minimum quota constraints, to optimize load balancing in integrated mmW-microwave networks. Fifth, a novel medium access control (MAC) protocol is proposed to dynamically manage the wireless local area network (WLAN) traffic jointly over the unlicensed 60 GHz mmW and sub-6 GHz bands to maximize the saturation throughput and minimize the delay experienced by users. Finally, a novel resource management approach is proposed to optimize device-to-device (D2D) communications and improve traffic offload in heterogeneous wireless SCNs by leveraging social context information that is dynamically learned by the network. In a nutshell, by providing novel, context-aware, and self-organizing frameworks, this dissertation addresses fundamentally challenging resource management problems that mainly stem from large scale, stringent service requirements, and heterogeneity of next-generation wireless networks. / Ph. D.

Les futures applications sans fil anticipent une explosion de la pléthore de cas d'utilisation et de services, qui ne peut être soutenue par des améliorations incrémentielles des schémas de communication existants. Pour cela, deux axes de recherche sont particulièrement intéressants: la densification du réseau à l'aide de petites cellules et la communication par ondes millimétriques (ondes millimétriques). Dans cette thèse, nous modélisons et évaluons des réseaux cellulaires constitués de petites cellules à ondes millimétriques utilisant la technique d'accès multi-radio (RAT) déployées au-dessus de la macro-architecture existante. Premièrement, nous modélisons mathématiquement un déploiement homogène de petites cellules multi-RAT et caractérisons les performances de l'utilisateur et du réseau en termes de probabilité de couverture signal sur brouillage plus rapport de bruit (SINR), de débit descendant et de probabilité de surcharge de cellule. Ensuite, nous étudions l'association des utilisateurs à différents niveaux et la sélection optimale de différents RAT, de manière à optimiser ces mesures de performance. En règle générale, les modèles de réseau cellulaire qui supposent des déploiements homogènes de petites cellules ne tiennent pas compte des nuances des caractéristiques de blocage urbain. Pour résoudre ce problème, nous modélisons les emplacements de petites cellules le long des routes d'une ville, puis nous prenons en compte les blocages de signaux dus à la construction d'immeubles ou au déplacement de véhicules sur les routes. Sur ce réseau, nous supposons que l’opérateur prend en charge trois types de services v.i.z., les communications ultra-fiables à faible temps de latence (URLLC), les communications massives de type machine (mMTC) et le haut débit mobile amélioré (eMBB) avec des besoins différents. En conséquence, nous étudions la sélection optimale de RAT pour ces services avec divers blocages de véhicules. Enfin, sur la base du modèle de déploiement sur route de petites cellules à ondes millimétriques, nous étudions un réseau conçu pour prendre en charge simultanément des services de positionnement et de données. Nous caractérisons la précision du positionnement en fonction des limites de la localisation, puis étudions des stratégies optimales de partitionnement des ressources et de sélection de la largeur de faisceau afin de répondre à diverses exigences de positionnement et de débit de données. / Future wireless applications anticipate an explosion in the plethora of use-cases and services, which cannot be sustained by incremental improvements on the existing communication schemes. For this, two research directions are particularly attractive: network densification using small cells and millimeter wave (mm-wave) wave communications. In this thesis, we model and evaluate cellular networks consisting of multi-radio access technique (RAT) mm-wave small cells deployed on top of the legacy macro-architecture. First, we mathematically model a homogeneous deployment of multi-RAT small cells and characterize the user and network performance in terms of signal to interference plus noise ratio (SINR) coverage probability, downlink throughput, and the cell overloading probability. Then, we study users association to different tiers and optimal selection of different RATs, so as to optimize these performance metrics. Generally, cellular network models that assume homogeneous deployments of small cells fail to take into account the nuances of urban blockage characteristics. To address this, we model the small cell locations along the roads of a city, and subsequently, we take into consideration the signal blockages due to buildings or moving vehicles on the roads. In this network, we assume that the operator supports three types of services v.i.z., ultra-reliable low-latency communications (URLLC), massive machine-type communications (mMTC), and enhanced mobile broadband (eMBB) with different requirements. Consequently, we study the optimal RAT selection for these services with varying vehicular blockages. Finally, based on the on-road deployment model of mm-wave small cells, we study a network designed to support positioning and data services simultaneously. We characterize the positioning accuracy based on the localization bounds and then study optimal resource partitioning and beamwidth selection strategies to address varied positioning and data-rate requirements.

Wireless network virtualization (WNV) and millimeter wave (mmW) communications are emerging as two key technologies for cellular networks. Virtualization in cellular networks enables wireless services to be decoupled from network resources (e.g., infrastructure and spectrum) so that multiple virtual networks can be built using a shared pool of network resources. At the same time, utilization of the large bandwidth available in mmW frequency band would help to overcome ongoing spectrum scarcity issues. In this context, this dissertation presents efficient frameworks for building virtual networks in sub-6 GHz and mmW bands. Towards developing the frameworks, first, we derive a closed-form expression for the downlink rate coverage probability of a typical sub-6 GHz cellular network with known base station (BS) locations and stochastic user equipment (UE) locations and channel conditions. Then, using the closed-form expression, we develop a sub-6 GHz virtual resource allocation framework that aggregates, slices, and allocates the sub-6 Ghz network resources to the virtual networks in such a way that the virtual networks' sub-6 GHz downlink coverage and rate demands are probabilistically satisfied while resource over-provisioning is minimized in the presence of uncertainty in UE locations and channel conditions. Furthermore, considering the possibility of lack of sufficient sub-6 GHz resources to satisfy the rate coverage demands of all virtual networks, we design a prioritized sub-6 GHz virtual resource allocation scheme where virtual networks are built sequentially based on their given priorities. To this end, we develop static frameworks that allocate sub-6 GHz resources in the presence of uncertainty in UE locations and channel conditions, i.e., before the UE locations and channel conditions are revealed. As a result, when a slice of a BS serves its associated UEs, it can be over-satisfied (i.e., resources left after satisfying the rate demands of all UEs) or under-satisfied (i.e., lack of resources to satisfy the rate demands of all UEs). On the other hand, it is extremely challenging to execute the entire virtual resource allocation process in real time due to the small transmission time intervals (TTIs) of cellular technologies. Taking this into consideration, we develop an efficient scheme that performs the virtual resource allocation in two phases, i.e., virtual network deployment phase (static) and statistical multiplexing phase (adaptive). In the virtual network deployment phase, sub-6 GHz resources are aggregated, sliced, and allocated to the virtual networks considering the presence of uncertainty in UE locations and channel conditions, without knowing which realization of UE locations and channel conditions will occur. Once the virtual networks are deployed, each of the aggregated BSs performs statistical multiplexing, i.e., allocates excess resources from the over-satisfied slices to the under-satisfied slices, according to the realized channel conditions of associated UEs. In this way, we further improve the sub-6 GHz resource utilization. Next, we steer our focus on the mmW virtual resource allocation process. MmW systems typically use beamforming techniques to compensate for the high pathloss. The directional communication in the presence of uncertainty in UE locations and channel conditions, make maintaining connectivity and performing initial access and cell discovery challenging. To address these challenges, we develop an efficient framework for mmW virtual network deployment and UE assignment. The deployment decisions (i.e., the required set of mmW BSs and their optimal beam directions) are taken in the presence of uncertainty in UE locations and channel conditions, i.e., before the UE locations and channel conditions are revealed. Once the virtual networks are deployed, an optimal mmW link (or a fallback sub-6 GHz link) is assigned to each UE according to the realized UE locations and channel conditions. Our numerical results demonstrate the gains brought by our proposed scheme in terms of minimizing resource over-provisioning while probabilistically satisfying virtual networks' sub-6 GHz and mmW demands in the presence of uncertainty in UE locations and channel conditions. / Doctor of Philosophy / In cellular networks, mobile network operators (MNOs) have been sharing resources (e.g., infrastructure and spectrum) as a solution to extend coverage, increase capacity, and decrease expenditures. Recently, due to the advent of 5G wireless services with enormous coverage and capacity demands and potential revenue losses due to over-provisioning to serve peak demands, the motivation for sharing and virtualization has significantly increased in cellular networks. Through wireless network virtualization (WNV), wireless services can be decoupled from the network resources so that various services can efficiently share the resources. At the same time, utilization of the large bandwidth available in millimeter wave (mmW) frequency band would help to overcome ongoing spectrum scarcity issues. However, due to the inherent features of cellular networks, i.e., the uncertainty in user equipment (UE) locations and channel conditions, enabling WNV and mmW communications in cellular networks is a challenging task. Specifically, we need to build the virtual networks in such a way that UE demands are satisfied, isolation among the virtual networks are maintained, and resource over-provisioning is minimized in the presence of uncertainty in UE locations and channel conditions. In addition, the mmW channels experience higher attenuation and blockage due to their small wavelengths compared to conventional sub-6 GHz channels. To compensate for the high pathloss, mmW systems typically use beamforming techniques. The directional communication in the presence of uncertainty in UE locations and channel conditions, make maintaining connectivity and performing initial access and cell discovery challenging. Our goal is to address these challenges and develop optimization frameworks to efficiently enable virtualization and mmW technologies in cellular networks.

Abstract The past two decades have witnessed an unprecedented proliferation of mobile devices equipped with extremely innovative wireless technologies. Short range networks, such as wireless personal area networks (WPANs), wireless sensor networks (WSNs) and wireless body area networks (WBANs) have been defined and researched to deliver high speed home connectivity, environment and health monitoring. This thesis tackles design, analysis and simulation of medium access control (MAC) protocols tailored for short range networks. These have in common the use of battery operated devices but also certain design challenges connected with MAC protocols are common upon selecting the physical layer technology. Ultra wideband (UWB) technology and 60 GHz technology (which is referred to also as millimeter wave communications) are two valid examples of the wireless revolution of the past decade. Several existing standards, such as IEEE 802.15.3, ECMA-368, IEEE 802.15.4 and its amendment IEEE 802.15.4a, are considered in this thesis for MAC analysis in conjunction with UWB technology. With regard to millimeter wave communications the characteristics of the IEEE 802.15.3c standard are taken into account. Apart for the IEEE 802.15.3c all the MAC protocols have been modeled in the network simulator Opnet. One contribution of this thesis is to produce an innovative and in-depth analysis of the management aspects (e.g. ECMA-368 distributed beaconing) stemming from the above mentioned standards by means of analytical and simulation models. This study approach allows selecting the MAC features suitable for the applications and the technologies of interest. The key performance metric used to analyze all the protocols is energy efficiency, but also throughput is investigated. Another contribution brought by this thesis consists in the innovative way of studying slotted-based MAC protocols as an integrated concept connected with the type of network, the type of application and the selected physical technologies. This thesis also shows MAC performance in conjunction with UWB when false alarm, miss-detection and receiver capture (capture is modeled by means of an existing interference model) are taken into consideration. Most of the unrealistic, though common, assumptions in MAC analysis are removed and the performance of selected medical applications is evaluated through Opnet simulations. The well known binary exponential backoff is analyzed with an innovative though simplified one-dimensional Markov chain approach in the context of directional MAC for 60 GHz communications. As shown in the remainder of this thesis, the simplification introduced does not hinder the accuracy of the results, but rather allows accounting even for a finite number of retransmissions with a simple chain extension. / Tiivistelmä Kahden viime vuosikymmenen aikana innovatiivisella langattomalla tekniikalla varustettujen viestintälaiteiden määrä on kasvanut räjähdysmäisesti. Lyhyen kantaman verkkoja kuten langattomia henkilökohtaisen alueen verkkoja (WPAN), langattomia anturiverkkoja (WSN) ja langattomia vartaloalueen verkkoja (WBAN) on määritelty ja tutkittu, jotta voitaisiin tuottaa korkeanopeuksisia kotiyhteyksiä sekä välineitä ympäristön ja terveydentilan seurantaan. Tämä väitöskirja käsittelee lyhyen kantaman viestintään suunniteltujen linkinohjauskerroksen MAC-protokollien suunnittelua, analysointia ja simulointia. Näissä kaikissa käytetään akkukäyttöisiä laitteita, mutta myös tietyt MAC-protokollien suunnittelun haasteet ovat tavallisia fyysisen kerroksen teknologiaa valittaessa. Ultra-laajakaistainen (UWB) teknologia ja 60 GHz teknologia (eli millimetriaallonpituusalueen tietoliikenne) ovat hyviä esimerkkejä kuluneen vuosikymmenen langattomasta vallankumouksesta. Tässä väitöskirjassa huomioidaan UWB teknologiaan liittyvää MAC-kerroksen analyysiä tehtäessä useat olemassa olevat standardit, kuten IEEE 802.15.3, ECMA-368, IEEE 802.15.4 ja sen lisäys IEEE 802.15.4a. Millimetriaallonpituusalueen tietoliikenteessä huomioidaan myös IEEE 802.15.3c standardin erityispiirteet. IEEE 802.15.3c:tä lukuun ottamatta kaikki MAC-protokollat on mallinnettu Opnet verkkosimulaattorilla. Tämä tutkimus tarjoaa innovatiivisen ja syväluotaavan tutkimuksen näiden standardien pohjalta ja analyyttisten ja simuloitujen mallien avulla kehitetyistä hallinnallisista lähestymistavoista (esim. ECMA-368 hajautettu majakkasignaali). Näiden avulla voidaan valita kohteena oleviin sovelluksiin ja teknologioihin parhaiten soveltuvia MAC-ominaisuuksia. Kaikkien protokollien analysointiin käytetty ensisijainen suorituskykymittari on energiatehokkuus, mutta myös datanopeuksia on tarkasteltu. Tässä tutkimuksessa esitellään myös innovatiivinen tapa tutkia MAC protokollia integroituina konsepteina suhteessa verkon ja sovellusten tyyppiin sekä fyysisen kerroksen teknologiaan. Lisäksi tämä väitöskirja esittelee MAC suorituskykyä UWB verkossa silloin, kun siinä otetaan huomioon väärät hälytykset, väärä havainnointi ja vastaanottimen signaalinkaappaus (vastaanoton mallintamiseksi käytetään olemassa olevaa interferenssimallia). MAC analyysistä poistetaan useimmat epärealistiset, vaikkakin tavalliset, olettamukset, ja verkkojen suorituskykyä tarkastellaan valittujen kriittisten parametrien monitoroinnissa Opnet-simulaatioiden avulla. Tunnettua binäärijakoinen eksponentiaalinen perääntyminen -algoritmia analysoidaan innovatiivisella, yksinkertaistetulla yksiulotteisella Markov-ketju -mallilla 60 GHz:n suunta-antenni MAC:n yhteydessä. Kuten tässä tutkimuksessa tullaan osoittamaan, esitelty yksinkertaistus ei rajoita tulosten tarkkuutta, vaan mukaan voidaan lukea jopa rajallinen määrä uudelleenlähetyksiä yksinkertaisen Markovin ketjun laajennuksen avulla.