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

Das traditionell gewachsene System der deutschen Gesundheitsversorgung gliedert sich in den stationären und niedergelassenen Bereich. Stand der Technik ist es in beiden Bereichen die Vorteile der elektronischen Verarbeitung der Patientendaten zu nutzen. Defizite gibt es jedoch bei der elektronischen Kommunikation zwischen den beiden Teilbereichen. Dies liegt zum einen an der komplexen Gesetzeslage, zum anderen an den vielfältigen Anforderungen einer technischen Umsetzung der sektorübergreifenden Kommunikation. Hier setzt die vorliegende Arbeit an, indem ein Katalog für die gesetzlichen, technischen und ökonomischen Anforderungen erstellt wird. Für den elektronischen Datenaustausch gibt es zahlreiche etablierte Verfahren, wie z.B. die E-Mail-Kommunikation. Es werden einige weit verbreitete aber auch speziell auf die Gegebenheiten des deutschen Gesundheitswesens zugeschnittene Verfahren vorgestellt und den Anforderungen gegenübergestellt. Ziel der Untersuchung ist die Ermittlung eines anforderungskonformen Verfahrens. Die auf diese Weise gewonnenen Erkenntnisse werden bei der Erstellung eines Referenzmodells für die Kommunikation zwischen stationären und ambulanten Bereich genutzt. Dabei wird ein schrittweises Vorgehen verfolgt. Zunächst werden mit UML Use Case Diagrammen Anwendungsfälle analysiert. Anschließend werden mit Hilfe von Sequenzdiagrammen die Kommunikationsprozessabläufe modelliert. Alle Erkenntnisse münden in der Erstellung eines Drei-Ebenen-Modells. Das 3LGM2-Referenzmodell soll dem Informationsmanager in einem Krankenhauses bei der Modellierung des Informationsflusses zwischen den Einrichtungen des Gesundheitswesens unterstützen.

Le trafic mobile global atteindra 24,3 exa-octets en 2019. Accueillir cette croissance dans les réseaux d’accès radio devient un véritable casse-tête. Nous porterons donc toute notre attention sur l'une des solutions à ce problème : le délestage (offloading) grâce à des communications de dispositif à dispositif (D2D). Notre première contribution est DROiD, une stratégie qui exploite la disponibilité de l'infrastructure cellulaire comme un canal de retour afin de suivre l'évolution de la diffusion d’un contenu. DROiD s’adapte au rythme de la diffusion, permettant d'économiser une quantité élevée de données cellulaires, même dans le cas de contraintes de réception très serrées. Ensuite, nous mettons l'accent sur les gains que les communications D2D pourraient apporter si elles étaient couplées avec les transmissions multicast. Par l’utilisation équilibrée d'un mix de multicast, et de communications D2D, nous pouvons améliorer, à la fois, l'efficacité spectrale ainsi que la charge du réseau. Afin de permettre l’adaptation aux conditions réelles, nous élaborons une stratégie d'apprentissage basée sur l'algorithme dit ‘’bandit manchot’’ pour identifier la meilleure combinaison de communications multicast et D2D. Enfin, nous mettrons en avant des modèles de coûts pour les opérateurs, désireux de récompenser les utilisateurs qui coopèrent dans le délestage D2D. Nous proposons, pour cela, de séparer la notion de seeders (utilisateurs qui transportent contenu, mais ne le distribuent pas) et de forwarders (utilisateurs qui sont chargés de distribuer le contenu). Avec l'aide d’un outil analytique basée sur le principe maximal de Pontryagin, nous développons une stratégie optimale de délestage. / Mobile data traffic is expected to reach 24.3 exabytes by 2019. Accommodating this growth in a traditional way would require major investments in the radio access network. In this thesis, we turn our attention to an unconventional solution: mobile data offloading through device-to-device (D2D) communications. Our first contribution is DROiD, an offloading strategy that exploits the availability of the cellular infrastructure as a feedback channel. DROiD adapts the injection strategy to the pace of the dissemination, resulting at the same time reactive and relatively simple, allowing to save a relevant amount of data traffic even in the case of tight delivery delay constraints.Then, we shift the focus to the gains that D2D communications could bring if coupled with multicast wireless networks. We demonstrate that by employing a wise balance of multicast and D2D communications we can improve both the spectral efficiency and the load in cellular networks. In order to let the network adapt to current conditions, we devise a learning strategy based on the multi-armed bandit algorithm to identify the best mix of multicast and D2D communications. Finally, we investigate the cost models for operators wanting to reward users who cooperate in D2D offloading. We propose separating the notion of seeders (users that carry content but do not distribute it) and forwarders (users that are tasked to distribute content). With the aid of the analytic framework based on Pontryagin's Maximum Principle, we develop an optimal offloading strategy. Results provide us with an insight on the interactions between seeders, forwarders, and the evolution of data dissemination.

Cooperative transmission involves the simultaneous transmission by a group of devices, alldevices sending the same data. The devices may use sidelink (SL) to share data prior to thejoint transmission. Cooperative transmission helps improve network coverage since it can usethe combined transmission power of all devices in a group, whereas single-hop transmissionby one device is limited to its own maximum uplink power. Cooperative transmission aim is toimprove the network coverage of devices involved. The cooperative transmission solutioncomprisestwo steps. The first step is when a device (source device) in the group wants to senddata in the UL and then transmits data via SL to the devices in a created group. In the secondstep, all users simultaneously transmit the data in the UL to the base station the group isassigned to.This master thesis studies both the performance in the uplink (UL), comparing cooperativewith direct transmission, and how to reduce the power consumption of the devices involvedin the cooperative transmission.A power consumption model was developed to analyze the energy consumption, both viaanalytical and simulations methods. The analytical results show that cooperative transmissioncan reduce energy consumption by 7% compared to direct transmission. An algorithm wasproposed for cooperative transmission, which helps reduce energy consumption by 31%.Furthermore, the performance of cooperative transmissions was also studied using a systemsimulator. The results shows that the UL total bit rate increases with cooperative transmissionand is proportional to the number of users in the group. The total bit rate increased by 57%for a group with five users and for a group of 10 the increase was 107% (with a carrierfrequency of 3GHz). Different scenarios were simulated, and the increase in total bit ratevaries from 50-150%. Cooperative transmission involves the simultaneous transmission by a group of devices, alldevices sending the same data. The devices may use sidelink (SL) to share data prior to thejoint transmission. Cooperative transmission helps improve network coverage since it can usethe combined transmission power of all devices in a group, whereas single-hop transmissionby one device is limited to its own maximum uplink power. Cooperative transmission aim is toimprove the network coverage of devices involved. The cooperative transmission solutioncomprisestwo steps. The first step is when a device (source device) in the group wants to senddata in the UL and then transmits data via SL to the devices in a created group. In the secondstep, all users simultaneously transmit the data in the UL to the base station the group isassigned to.This master thesis studies both the performance in the uplink (UL), comparing cooperativewith direct transmission, and how to reduce the power consumption of the devices involvedin the cooperative transmission.A power consumption model was developed to analyze the energy consumption, both viaanalytical and simulations methods. The analytical results show that cooperative transmissioncan reduce energy consumption by 7% compared to direct transmission. An algorithm wasproposed for cooperative transmission, which helps reduce energy consumption by 31%.Furthermore, the performance of cooperative transmissions was also studied using a systemsimulator. The results shows that the UL total bit rate increases with cooperative transmissionand is proportional to the number of users in the group. The total bit rate increased by 57%for a group with five users and for a group of 10 the increase was 107% (with a carrierfrequency of 3GHz). Different scenarios were simulated, and the increase in total bit ratevaries from 50-150%.

With the increasing demand for wireless communications, radio resource management (RRM) plays an important role in future wireless networks in order to provide higher data rates and better quality of services, given the limited amount of available radio resources. Although some specific features of wireless communication networks cause challenges to effective and efficient RRM, they bring opportunities that help improv- ing network performance and resource utilization. In this thesis, we focus on RRM issues related to the broadcast/multicast nature in wireless communication networks. The work is divided into two parts. In the first part, we exploit how to take advantage of the broadcast nature of wire- less transmissions in RRM by opportunistically applying two-way relaying (or network coding) and traditional one-way relaying. Different objectives are considered, includ- ing maximizing total packet transmission throughput (Chapter 2), minimizing costs related to transmission power and delay (Chapter 3), and minimizing packet transmis- sion delay subject to maximum and average transmission power limits (Chapter 4). While designing these scheduling schemes, the random traffic and channel conditions are also taken into consideration. Our results show that the proposed opportunis- tic scheduling schemes can indeed take good advantage of the broadcast feature at the relay nodes and achieve much higher throughput and, in some scenarios, provide close-to-optimum QoS performance. The second part (Chapter 5) of the thesis deals with the issue of efficient resource management in multicast communications, where we study channel sharing and power allocations for multicast device-to-divice (D2D) communication groups underlaying a cellular network. In such a scenario, D2D multicasting together with the mutual inter- ference between cellular and D2D communications, makes the interference conditions and power allocations a very complicated issue. Different approaches are proposed that allow each D2D group to share the cellular channels and allocate transmission power to each D2D and cellular transmitter, so that the sum throughput of D2D and cellular users is maximized. Our results indicate that it is possible to achieve close-to-optimum throughput performance in such a network. / Dissertation / Doctor of Philosophy (PhD)

In the literature, Cognitive radio (CR) as well as full-duplex (FD) communication technologies are proposed to increase the spectrum efficiency. The main contribution of this thesis is to introduce prediction and estimation techniques with low control overhead, and use the predicted or estimated information in resource allocation in CR networks, both in the overlay networks and the underlay networks. Prediction and estimation are important in increasing the data rate and keeping the interference at a low level. In the overlay scheme, I modeled the primary user (PU) traffic characteristics of the channels using the Probabilistic Suffix Tree (PST) algorithm. Then using this PST algorithm, I introduced a frequency hopping based control channel and derived its theoretical properties. Then I proposed two methods for selecting a channel set for transmission, which took into account both the PU channel usage statistics and, secondary user (SU) channel usage statistics as perceived by an SU of interest. The first scheme selected channels having the highest probability of successful transmission, while the second calculated a net reward using a marked Markov chain. Then using simulations, I showed that our scheme caused acceptable interference to the PUs and has better throughput performance, compared to a scheme selecting channels randomly. Then I proposed two joint channel assignment and power allocation schemes for a bi-directional FD underlay CR network with network assistance. The first scheme used the information on the number of total SU pairs present in the network. In the second scheme, I used least squares based estimation and Kalman filtering to estimate the interference at the monitoring stations using the local interference. It reduced the control overhead of keeping track of active SUs. In both of these schemes each SU pair decided on the channels to be used in the half-duplex mode and the full-duplex mode using local information. This joint optimization was done running channel assignment and power allocation algorithms alternatively. In the power allocation problem, I used a technique called monotonic optimization. After simulating both of these schemes I showed that the scheme based on estimation performs satisfactorily given that it has less control overhead. / October 2016

No description available.

Det studien har identifierat är en avsaknad av sammanställda risker och fördelar för den vanligaste organisationstypen i många länder; SMEs (small and medium-sized enterprises). Det existerar inga sammanfattade hjälpmedel för utveckling och implementation för IoT (Internet of Things) som understöd åt beslutsstödsystem (ERP_DSS) för målgruppen SMEs. Det studien presenterar är ett ramverk med fördelar som rekommenderas att följas och risker som rekommenderas att undvikas, vid utveckling och implementation av IoT som understöd åt beslutsstödsystem. Studien har också praktiskt prövat användbarheten av ramverket genom design science, där prototyper utvecklats. Ramverkets användbarhet kan efter lyckad utveckling av protyper och ytterligare identifierade risker, presentera ett fungerande och sammanställt hjälpmedel för målgruppen SMEs.

Abstract Future cellular networks need to support the ever-increasing demand of bandwidth-intensive applications and interconnection of people, devices, and vehicles. Small cell network (SCN)-based communication together with proximity- and social-aware connectivity is conceived as a vital component of these networks to enhancing spectral efficiency, system capacity, and quality-of-experience (QoE). To cope with diverse application needs for the heterogeneous ecosystem, radio resource management (RRM) is one of the key research areas for the fifth-generation (5G) network. The key goals of this thesis are to develop novel, self-organizing, and low-complexity resource management algorithms for emerging device-to-device (D2D) and vehicle-to-vehicle (V2V) wireless systems while explicitly modeling and factoring network contextual information to satisfy the increasingly stringent requirements. Towards achieving this goal, this dissertation makes a number of key contributions. First, the thesis focuses on interference management techniques for D2D-enabled macro network and D2D-enabled SCNs in the downlink, while leveraging users’ social-ties, dynamic clustering, and user association mechanisms for network capacity maximization. A flexible social-aware user association technique is proposed to maximize network capacity. The second contribution focuses on ultra-reliable low-latency communication (URLLC) in vehicular networks in which interference management and resource allocation techniques are investigated, taking into account traffic and network dynamics. A joint power control and resource allocation mechanism is proposed to minimize the total transmission power while satisfying URLLC constraints. To overcome these challenges, novel algorithms are developed by combining several methodologies from graph theory, matching theory and Lyapunov optimization. Extensive simulations validate the performance of the proposed approaches, outperforming state-of-the-art solutions. Notably, the results yield significant performance gains in terms of capacity, delay reductions, and improved reliability as compared with conventional approaches. / Tiivistelmä Tulevaisuuden solukkoverkkojen pitää pystyä tukemaan yhä suurempaa kaistanleveyttä vaativia sovelluksia sekä yhteyksiä ihmisten, laitteiden ja ajoneuvojen välillä. Piensoluverkkoihin (SCN) pohjautuvaa tietoliikennettä yhdistettynä paikka- ja sosiaalisen tietoisuuden huomioiviin verkkoratkaisuihin pidetään yhtenä elintärkeänä osana tulevaisuuden solukkoverkkoja, joilla pyritään tehostamaan spektrinkäytön tehokkuutta, järjestelmän kapasiteettia sekä kokemuksen laatua (QoE). Radioresurssien hallinta (RRM) on eräs keskeisistä viidennen sukupolven (5G) verkkoihin liittyvistä tutkimusalueista, joilla pyritään hallitsemaan heterogeenisen ekosysteemin vaihtelevia sovellustarpeita. Tämän väitöstyön keskeisinä tavoitteina on kehittää uudenlaisia itseorganisoituvia ja vähäisen kompleksisuuden resurssienhallinta-algoritmeja laitteesta-laitteeseen (D2D) ja ajoneuvosta-ajoneuvoon (V2V) toimiville uusille langattomille järjestelmille, sekä samalla mallintaa ja tuottaa verkon kontekstikohtaista tietoa vastaamaan koko ajan tiukentuviin vaatimuksiin. Tämä väitöskirja edistää näiden tavoitteiden saavuttamista usealla keskeisellä tuloksella. Aluksi väitöstyössä keskitytään häiriönhallinnan tekniikoihin D2D:tä tukevissa makroverkoissa ja laskevan siirtotien piensoluverkoissa. Käyttäjän sosiaalisia yhteyksiä, dynaamisia ryhmiä sekä osallistamismekanismeja hyödynnetään verkon kapasiteetin maksimointiin. Verkon kapasiteettia voidaan kasvattaa käyttämällä joustavaa sosiaaliseen tietoisuuteen perustuvaa osallistamista. Toinen merkittävä tulos keskittyy huippuluotettavaan lyhyen viiveen kommunikaatioon (URLLC) ajoneuvojen verkoissa, joissa tehtävää resurssien allokointia ja häiriönhallintaa tutkitaan liikenteen ja verkon dynamiikka huomioiden. Yhteistä tehonsäädön ja resurssien allokoinnin mekanismia ehdotetaan kokonaislähetystehon minimoimiseksi samalla, kun URLLC rajoitteita noudatetaan. Jotta esitettyihin haasteisiin voidaan vastata, väitöstyössä on kehitetty uudenlaisia algoritmeja yhdistämällä graafi- ja sovitusteorioiden sekä Lyapunovin optimoinnin menetelmiä. Laajat tietokonesimuloinnit vahvistavat ehdotettujen lähestymistapojen suorituskyvyn, joka on parempi kuin uusimmilla nykyisillä ratkaisuilla. Tulokset tuovat merkittäviä suorituskyvyn parannuksia erityisesti kapasiteetin lisäämisen, viiveiden vähentämisen ja parantuneen luotettavuuden suhteen verrattuna perinteisiin lähestymistapoihin.

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