Wireless communication systems are growing at an unprecedented pace, making the wireless spectrum at a premium, especially as billions of new Internet-of-Things (IoT) devices worldwide are demanding wireless connections. To accommodate the ever-growing spectrum demand, a promising solution is Non-Orthogonal Multiple Access (NOMA) that enables two users to communicate with the same spectrum resource at the same time, while decoding the two-user superimposed signal at the receiver. By doing this, the previously detrimental wireless interference caused by two concurrent transmitters becomes decodable at the receiver, potential for higher utilization of the wireless spectrum. Existing NOMA technologies, however, rely on strict power control to sequentially decode the two-user superimposed signal, which is infeasible for many IoT devices that are heterogeneous and often low-cost. In contrast, in this dissertation, we propose new NOMA schemes that are designed for wireless communication systems and can decode the two-user superimposed signals without power control. This dissertation makes four major contributions. First, it presents the first design to implement dynamic signal offsets tracking and reacting schemes to detect and decode two-user superimposed signals, robust against hardware imperfections and feasible for heterogeneous IoT devices. Second, by investigating the relationship between the channel condition and the bit-error-rate (BER) in decoding superimposed signals, we design a reliable NOMA scheme to combat dynamic channel conditions that are inevitable in many practical scenarios and may cause severe decoding errors. Third, considering the wireless communication systems in mobile scenarios, mobility is a vital feature of many applications but can cause severe signal variations and make the hardware offsets harder to predict, resulting in an unreliable decoding performance. To address this, we develop a diversity transmission and smart combining scheme to achieve high reliable decoding performance. Finally, we combine rotation coding to transmit and decode the superimposed signal to achieve both high spectrum efficiency and high reliability performance. To demonstrate our contributions, we derive the theoretical relationship of the BER under different practical settings, validate the performance with simulations, and conduct experiments using software-defined radio based platforms with static indoor, outdoor scenarios and mobile scenarios. The experimental results demonstrate that, compared with the state-of-the-art methods, our schemes can achieve higher reliability and spectrum efficiency in decoding the superimposed signal for wireless communication systems without power control. / Graduate

This thesis identifies and addresses two barriers to the adoption of Long Term Evolution (LTE) Device-to-Device (D2D) communication enabled smart grid applications in out of core network coverage regions. The first barrier is the lack of accessible simulation software for engineers to develop and test the feasibility of their D2D LTE enabled smart grid application designs. The second barrier is the lack of a distributed resource allocation algorithm for LTE D2D communications that has been tailored to the needs of smart grid applications. A solution was proposed to the first barrier in the form of a simulator constructed in Matlab/Simulink used to simulate power systems and the underlying communication system, i.e., D2D communication protocol stack of Long Term Evolution (LTE). The simulator is built using Matlab's LTE System Toolbox, SimEvents, and Simscape Power Systems in addition to an in-house developed interface software to facilitate D2D communications in smart grid applications. To test the simulator, a simple fault location, isolation, and restoration (FLISR) application was implemented using the simulator to show that the LTE message timing is consistent with the relay signaling in the power system. A solution was proposed to the second barrier in the form of a multi-agent Q-learning based resource allocation algorithm that allows Long Term Evolution (LTE) enabled device-to-device (D2D) communication agents to generate orthogonal transmission schedules outside of network coverage. This algorithm reduces packet drop rates (PDR) in distributed D2D communication networks to meet the quality of service requirements of microgrid communications. The PDR and latency performance of the proposed algorithm was compared to the existing random self-allocation mechanism introduced under the Third Generation Partnership Project's LTE Release 12. The proposed algorithm outperformed the LTE algorithm for all tested scenarios, demonstrating 20-40% absolute reductions in PDR and 10-20 ms reductions in latency for all microgrid applications.

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.

It is foreseeable that device-to-device (D2D) communication will become a standard feature in the future, for the reason that it offloads the data traffic from network infrastructures to user devices. Recent researches prove that delivering delay-tolerant contents through content delivery network (CDN) by D2D helps network operators increase spectral and energy efficiency. However, protecting the private information of mobile users in D2D assistant CDN is the primary concern, which directly affects the willingness of mobile users to share their resources with others. In this thesis, we proposed a privacy concerned top layer system for selecting the sub-optimal set of mobile nodes as initial mobile content provider (MCP) for content delivery in any general D2D communications, which implies that our proposed system does not rely on private user information such as location, affinity, and personal preferences. We model the initial content carrier set problem as an incentive maximization problem to optimize the rewards for network operators and content providers. Then, we utilized the Markov random field (MRF) theory to build a probabilistic graphical model to make an inference on the observation of delivered contents. Furthermore, we proposed a greedy algorithm to solve the non-linear binary integer programming (NLBIP) problem for selecting the optimal initial content carrier set. The evaluations of the proposed system are based on both a simulated dataset and a real-world collected dataset corresponding to the off-line and on-line scenarios.

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.

Face à la prolifération des technologies mobiles et à l’augmentation du volume des données utilisées par les applications mobiles, les périphériques consomment de plus en plus de bande passante. Dans cette thèse, nous nous concentrons sur les réseaux Wi-Fi denses comme cela peut être le cas lors d’événements à grande échelle (ex: conférences, séminaire, etc.) où un serveur doit acheminer des données à un grand nombre de périphériques dans une fenêtre temporelle réduite. Dans ce contexte, la consommation de bande passante et les interférences engendrées par les téléchargements parallèles d’une donnée volumineuse par plusieurs périphériques connectés au même réseau dégradent les performances. Les technologies de communication Device-to-Device (D2D) comme Bluetooth ou Wi-Fi Direct permettent de mieux exploiter les ressources du réseau et d’améliorer les performances pour offrir une meilleure qualité d’expérience (QoE) aux utilisateurs. Dans cette thèse nous proposons deux approches pour l’amélioration des performances de la dissémination de données. La première approche, plus adaptée à une configuration mobile, consiste à utiliser des connexions D2D en point-à-point sur une topologie plate pour les échanges de données. Nos évaluations montrent que notre approche permet de réduire les temps de dissémination jusqu’à 60% par rapport à l’utilisation du Wi-Fi seul. De plus, nous veillons à avoir une répartition équitable de la charge énergétique sur les périphériques afin de préserver les batteries les plus faibles du réseau. Nous avons pu voir qu’avec la prise en compte de l’autonomie des batteries et de la bande passante, la sollicitation des batteries les plus faibles peut être réduite de manière conséquente. La deuxième approche, plus adaptée à des configurations statiques, consiste à mettre en place des topologies hiérarchiques dans lesquelles on regroupe les périphériques par clusters. Dans chaque cluster, un périphérique est élu pour être le relais des données qu’il recevra depuis le serveur et qu’il transmettra à ses voisins. Cette approche permet de gérer plus efficacement les interférences en adaptant la puissance du signal afin de limiter la portée des clusters. Dans ce cas, nous avons observé jusqu’à 30 % de gains en temps de dissémination. Dans la continuité des travaux de cette thèse, nous discutons de plusieurs perspectives qu’il serait intéressant d’entreprendre par la suite, notamment l’adaptation automatique du protocole de dissémination à l’état du réseau et l’utilisation simultanée des deux types de topologie plate et hiérarchique. / We are witnessing a proliferation of mobile technologies and an increasing volume of data used by mobile applications. Devices consume thus more and more bandwidth. In this thesis, we focus on dense Wi-Fi networks during large-scale events (such as conferences). In this context, the bandwidth consumption and the interferences caused by the parallel downloads of a large volume of data by several mobile devices that are connected to the same Wi-Fi network degrade the performance of the dissemination. Device-to-Device (D2D) communication technologies such as Bluetooth or Wi-Fi Direct can be used in order to improve network performance to deliver better QoE to users. In this thesis we propose two approaches for improving the performance of data dissemination. The first approach, more suited to a dynamic configuration, is to use point-to-point D2D connections on a flat topology for data exchange. Our evaluations show that our approach can reduce dissemination times by up to 60% compared to using Wi-Fi alone. In addition, we ensure a fair distribution of the energy load on the devices to preserve the weakest batteries in the network. We have observed that by taking into account the battery life and the bandwidth of mobile devices, the solicitation of the weakest batteries can be reduced significantly. The second approach, more adapted to static configurations, consists in setting up hierarchical topologies by gathering mobile devices in small clusters. In each cluster, a device is chosen to relay the data that it receives from the server and forwards it to its neighbors. This approach helps to manage interference more efficiently by adjusting the signal strength in order to limit cluster reach. In this case, we observed up to 30% gains in dissemination time. In the continuity of this thesis work, we discuss three perspectives which would be interesting to be undertaken, in particular the automatic adaptation of the dissemination to the state of the network and the simultaneous use of both topology types, flat and hierarchical.

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abstract: Cognitive radio (CR) and device-to-device (D2D) systems are two promising dynamic spectrum access schemes in wireless communication systems to provide improved quality-of-service, and efficient spectrum utilization. This dissertation shows that both CR and D2D systems benefit from properly designed cooperation scheme. In underlay CR systems, where secondary users (SUs) transmit simultaneously with primary users (PUs), reliable communication is by all means guaranteed for PUs, which likely deteriorates SUs’ performance. To overcome this issue, cooperation exclusively among SUs is achieved through multi-user diversity (MUD), where each SU is subject to an instantaneous interference constraint at the primary receiver. Therefore, the active number of SUs satisfying this constraint is random. Under different user distributions with the same mean number of SUs, the stochastic ordering of SU performance metrics including bit error rate (BER), outage probability, and ergodic capacity are made possible even without observing closed form expressions. Furthermore, a cooperation is assumed between primary and secondary networks, where those SUs exceeding the interference constraint facilitate PU’s transmission by relaying its signal. A fundamental performance trade-off between primary and secondary networks is observed, and it is illustrated that the proposed scheme outperforms non-cooperative underlay CR systems in the sense of system overall BER and sum achievable rate. Similar to conventional cellular networks, CR systems suffer from an overloaded receiver having to manage signals from a large number of users. To address this issue, D2D communications has been proposed, where direct transmission links are established between users in close proximity to offload the system traffic. Several new cooperative spectrum access policies are proposed allowing coexistence of multiple D2D pairs in order to improve the spectral efficiency. Despite the additional interference, it is shown that both the cellular user’s (CU) and the individual D2D user's achievable rates can be improved simultaneously when the number of D2D pairs is below a certain threshold, resulting in a significant multiplexing gain in the sense of D2D sum rate. This threshold is quantified for different policies using second order approximations for the average achievable rates for both the CU and the individual D2D user. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2017

Robust communication is required to provide a safe airspace for the large numbers of unmanned aerial systems that are coming to the National Airspace System (NAS). This thesis explores methods for providing robust communication to large numbers of vehicles in the NAS. Automatic dependent surveillance-broadcast (ASD-B) is a transmission system that can transmit to and is currently required on all manned aircraft. Unfortunately, ADS-B suffers connectivity problems when supporting large numbers of unmanned aerial systems (UAS). The 5G Cellular protocol can support large numbers of UAS, but connectivity suffers with an increase in distance and interference. Using a 5G cellular and an ADS-B simulator we evaluate the advantages of a combined ADS-B and 5G Cellular transmission system compared to a 5G or ADS-B exclusive system. We also offer hybrid system recommendations that clarify the appropriate operation strategies or triggers that should prompt transitions between transmission systems in different environmental situations. The simulation results show message success and vehicle collision rates, with each messaging method investigated to show the case for a combined communication system. This study shows that a hybrid transmission system is a possible communication solution for UAS operating in beyond visual line of sight (BVLOS) environments.

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