Motivated by recent developments in wireless communication, this thesis aims to characterize the secrecy performance in several types of typical wireless networks. Advanced techniques are designed and evaluated to enhance physical layer security in these networks with realistic assumptions, such as signal propagation loss, random node distribution and non-instantaneous channel state information (CSI). The first part of the thesis investigates secret communication through relay-assisted cognitive interference channel. The primary and secondary base stations (PBS and SBS) communicate with the primary and secondary receivers (PR and SR) respectively in the presence of multiple eavesdroppers. The SBS is allowed to transmit simultaneously with the PBS over the same spectrum instead of waiting for an idle channel. To improve security, cognitive relays transmit cooperative jamming (CJ) signals to create additional interferences in the direction of the eavesdroppers. Two CJ schemes are proposed to improve the secrecy rate of cognitive interference channels depending on the structure of cooperative relays. In the scheme where the multiple-antenna relay transmits weighted jamming signals, the combined approach of CJ and beamforming is investigated. In the scheme with multiple relays transmitting weighted jamming signals, the combined approach of CJ and relay selection is analyzed. Numerical results show that both these two schemes are effective in improving physical layer security of cognitive interference channel. In the second part, the focus is shifted to physical layer security in a random wireless network where both legitimate and eavesdropping nodes are randomly distributed. Three scenarios are analyzed to investigate the impact of various factors on security. In scenario one, the basic scheme is studied without a protected zone and interference. The probability distribution function (PDF) of channel gain with both fading and path loss has been derived and further applied to derive secrecy connectivity and ergodic secrecy capacity. In the second scenario, we studied using a protected zone surrounding the source node to enhance security where interference is absent. Both the cases that eavesdroppers are aware and unaware of the protected zone boundary are investigated. Based on the above scenarios, further deployment of the protected zones at legitimate receivers is designed to convert detrimental interference into a beneficial factor. Numerical results are investigated to check the reliability of the PDF for reciprocal of channel gain and to analyze the impact of protected zones on secrecy performance. In the third part, physical layer security in the downlink transmission of cellular network is studied. To model the repulsive property of the cellular network planning, we assume that the base stations (BSs) follow the Mat´ern hard-core point process (HCPP), while the eavesdroppers are deployed as an independent Poisson point process (PPP). The distribution function of the distances from a typical point to the nodes of the HCPP is derived. The noise-limited and interference-limited cellular networks are investigated by applying the fractional frequency reuse (FFR) in the system. For the noise-limited network, we derive the secrecy outage probability with two different strategies, i.e. the best BS serve and the nearest BS serve, by analyzing the statistics of channel gains. For the interference-limited network with the nearest BS serve, two transmission schemes are analyzed, i.e., transmission with and without the FFR. Numerical results reveal that both the schemes of transmitting with the best BS and the application of the FFR are beneficial for physical layer security in the downlink cellular networks, while the improvement due to the application of the FFR is limited by the capacity of the legitimate channel.

abstract: Recently, the location of the nodes in wireless networks has been modeled as point processes. In this dissertation, various scenarios of wireless communications in large-scale networks modeled as point processes are considered. The first part of the dissertation considers signal reception and detection problems with symmetric alpha stable noise which is from an interfering network modeled as a Poisson point process. For the signal reception problem, the performance of space-time coding (STC) over fading channels with alpha stable noise is studied. We derive pairwise error probability (PEP) of orthogonal STCs. For general STCs, we propose a maximum-likelihood (ML) receiver, and its approximation. The resulting asymptotically optimal receiver (AOR) does not depend on noise parameters and is computationally simple, and close to the ML performance. Then, signal detection in coexisting wireless sensor networks (WSNs) is considered. We define a binary hypothesis testing problem for the signal detection in coexisting WSNs. For the problem, we introduce the ML detector and simpler alternatives. The proposed mixed-fractional lower order moment (FLOM) detector is computationally simple and close to the ML performance. Stochastic orders are binary relations defined on probability. The second part of the dissertation introduces stochastic ordering of interferences in large-scale networks modeled as point processes. Since closed-form results for the interference distributions for such networks are only available in limited cases, it is of interest to compare network interferences using stochastic. In this dissertation, conditions on the fading distribution and path-loss model are given to establish stochastic ordering between interferences. Moreover, Laplace functional (LF) ordering is defined between point processes and applied for comparing interference. Then, the LF orderings of general classes of point processes are introduced. It is also shown that the LF ordering is preserved when independent operations such as marking, thinning, random translation, and superposition are applied. The LF ordering of point processes is a useful tool for comparing spatial deployments of wireless networks and can be used to establish comparisons of several performance metrics such as coverage probability, achievable rate, and resource allocation even when closed form expressions for such metrics are unavailable. / Dissertation/Thesis / Ph.D. Electrical Engineering 2014

Channel State Information (CSI) refers to a set of measurements used to characterize a radio communication link. Radio infrastructure collects CSI and derives useful metrics that indicate changes to modulation and coding to be made to improve the link performance (e.g. throughput, reliability). The CSI, however, has a wider potential use. It contains an environment-specific signature that can be used to extract information about users’ position and activity. In our work, we explore the problem of proximity estimation, which consists of identifying how close a pair of devices are to each other. By assuming that Cellular Base Stations (BSs) are distributed spatially according to a Poisson Point Process (PPP), and that the channel is under Rayleigh fading, we were able to probabilistically model radio measurements and use Bayesian inference to estimate the separation between two devices given their measurements only. We first explore a shadowless channel model, then we investigate how spatially-correlated shadowing can prove useful for estimation. For both cases, Bayesian estimators are proposed and tested through simulations. We also perform experiments and evaluate how well the estimators fit to actual data.

Using drones for cellular coverage enhancement is a recent technology that has shown a great potential in various practical scenarios. However, one of the main challenges that limits the performance of drone-enabled wireless networks is the limited flight time. In particular, due to the limited on-board battery size, the drone needs to frequently interrupt its operation and fly back to a charging station to recharge/replace its battery. In addition, the charging station might be responsible to recharge multiple drones. Given that the charging station has limited capacity, it can only serve a finite number of drones simultaneously. Hence, in order to accurately capture the influence of the battery limitation on the performance, it is required to analyze the dynamics of the time spent by the drones at the charging stations. In this thesis, we first use tools from queuing theory and stochastic geometry to study the influence of each of the charging stations limited capacity and spatial density on the performance of a drone-enabled wireless network. We then extend our work to rural areas where users are greatly impacted by low income, high cost of backhaul connectivity, and limited resources. Considering the limitation of the electricity supply scarcity in some rural regions, we investigate the possibility and performance enhancement of the deployment of renewable energy (RE) charging stations. We outline three practical scenarios, and use simulation results to demonstrate that RE charging stations can be a possible solution to address the limited on-board battery of UAVs in rural areas, specially when they can harvest and store enough energy.

L'hétérogénéité et l’irrégularité croissante des déploiements des réseaux sans fil de nouvelles générations soulèvent des défis importants dans l’évaluation de performances de ces réseaux. Les modèles classiques s’appuyant sur des modèles hexagonaux pour décrire les emplacements géographiques des nœuds de transmission sont difficilement adaptables à ces réseaux. Dans ce contexte, il a été proposé un nouveau paradigme de modélisation des réseaux sans fil qui s’appuie sur les processus ponctuels de Poisson (PPP), et de manière générale sur la géométrie stochastique. L'analyse, au travers de ces outils mathématiques, présente une complexité indépendante de la taille du réseau, et permet d’estimer avec précision des quantités pratiques liées aux performances des réseaux cellulaires. Cette thèse a porté sur la faisabilité mathématique de l'approche fondée sur les PPP en proposant de nouvelles méthodes mathématiques d’approximations justes incorporant des modèles de propagation du canal radio. Dans un premier temps, un nouveau cadre mathématique, considéré comme une approche Equivalent-in-Distribution (EiD), a été proposée pour le calcul exact de la probabilité d'erreur dans les réseaux cellulaires. L'approche proposée, s’appuyant donc sur la géométrie aléatoire et des modèles spatiaux, montre une complexité faible en terme d’évaluation numérique et est applicable à un grand nombre de configurations MIMO pour lesquelles nous considérons différentes techniques de modulation et techniques de récupération du signal. Dans un deuxième temps, nous étudions les performances des réseaux cellulaires en présence de relais, où trois processus ponctuels de Poisson modélisent respectivement les nœuds relais, les stations de base, et les terminaux mobiles. Pour ce modèle, nous avons considéré des critères souples d'association. Le cadre mathématique proposé et les résultats associés ont montré que les performances dépendent fortement des exposants des fonctions d’atténuation sur les deux premiers sauts sans fil. Nous montrons aussi qu’une mauvaise configuration du réseau peut amener à des gains négligeables de l’utilisation de cette technique. Enfin, nous considérons la modélisation des réseaux cellulaires au travers d’un PPP et d’un modèle unifié d'atténuation de signal généralisée qui prend en compte deux types de liaisons physiques : line-of-sight (LOS) et non-line-of-sight (NLOS). Un modèle de complexité réduite décrivant les propriétés de la liaison radio a aussi été proposée et permet de prendre en compte dans nos calculs un grand nombre de modèle radio proposés dans la littérature. Les résultats montrent, entre autres, qu’une densité optimale pour le déploiement des BS existe lorsque les liens LOS/NLOS sont classés en fonction de leur charge. Nous comparons nos résultats, s’appuyant donc sur un PPP pour modéliser la position des stations de bases et notre modèle de canal radio, avec des simulations de Monte Carlo décrivant des déploiements réels de stations de bases et un modèle de type blocages de construction empiriques. Une bonne correspondance est observée. / The increasing heterogeneity and irregular deployment of the emerging wireless networks give enormous challenges to the conventional hexagonal model for abstracting the geographical locations of wireless transmission nodes. Against this backdrop, a new network paradigm by modeling the wireless nodes as a Poisson Point Process (PPP), leveraging on the mathematical tools of stochastic geometry for tractable mathematical analysis, has been proposed with the capability of fairly accurately estimating the performance of practical cellular networks. This dissertation investigated the mathematical tractability of the PPP-based approach by proposing new mathematical methodologies, fair approximations incorporating practical channel propagation models. First, a new mathematical framework, which is referred to as an Equivalent-in-Distribution (EiD)-based approach, has been proposed for computing exact error probability of cellular networks based on random spatial networks. The proposed approach is easy to compute and is shown to be applicable to a bunch of MIMO setups where the modulation techniques and signal recovery techniques are explicitly considered. Second, the performance of relay-aided cooperative cellular networks, where the relay nodes, the base stations, and the mobile terminals are modeled according to three independent PPPs, has been analyzed by assuming flexible cell association criteria. It is shown from the mathematical framework that the performance highly depends on the path-loss exponents of one-hop and two-hop links, and the relays provide negligible gains on the performance if the system is not adequately designed. Third, the PPP modeling of cellular networks with unified signal attenuation model is generalized by taking into account the effect of line-of-sight (LOS) and non-line-of-sight (NLOS) channel propagation. A tractable yet accurate link state model has been proposed to estimate other models available in the literature. It is shown that an optimal density for the BSs deployment exists when the LOS/NLOS links are classified in saturate load cellular networks. In addition, the Monte Carlo simulation results of the real BSs deployments with empirical building blockages are compared with those with PPP distributed BSs with the proposed link state approximation at the end of this dissertation as supplementary material. In general, a good matching is observed.

Vehicular communication is the enabling technology for the development of the intelligent transportation systems (ITS), which aims to improve the efficiency and safety of transportation. It can be used for a variety of useful applications such as adaptive traffic control, coordinated braking, emergency messaging, peer-to-peer networking for infotainment services and automatic toll collection etc... Accurate yet simple models for vehicular networks are required in order to understand and optimize their operation. For reliable communication between vehicles, the spectrum access is coordinated via carrier sense multiple access (CSMA) protocol. Existing models either use a simplified network abstraction and access control scheme for analysis or depend on simulation studies. Therefore it is important to develop an analytical model for CSMA coordinated communication between vehicles. In the first part of the thesis, stochastic geometry is exploited to develop a modeling framework for CSMA coordinated inter-vehicle communication (IVC) in a multi-lane highway scenario. The performance of IVC is studied in multi-lane highways taking into account the inter-lane separations and the number of traffic lanes and it is shown that for wide multi-lane highways, the line abstraction model that is widely used in literature loses accuracy and hence the analysis is not reliable. Since the analysis of CSMA in the vehicular setting makes the analysis intractable, an aggressive interference approximation and a conservative interference approximation is proposed for the probability of transmission success. These approximations are tight in the low traffic and high traffic densities respectively. In the subsequent part of the thesis, the developed model is extended to multi-hop IVC because several vehicular applications require going beyond the local communication and efficiently disseminate information across the roads via multi-hops. Two well-known greedy packet forwarding schemes are studied, that impose different tradeoffs between per-hop transmission success probability and forward packet progress, namely, the most forward with fixed radius (MFR) and the nearest with forward progress (NFP). In particular, a tractable and accurate modeling framework is developed to characterize the per-hop transmission success probability and the average forward progress for vehicular networks in a multi-lane highway setup. The developed model reveals the interplay between the spectrum sensing threshold of the CSMA protocol and the packet forwarding scheme. A new performance metric is defined, denoted as the aggregate packet progress (APP), which is a dimensionless quantity that captures the tradeoffs between the spatial frequency reuses efficiency, the per-hop transmission success probability, and the per-hop forward progress of the packets. To this end, in contrary to existing studies, the results show that with the proper manipulation of CSMA threshold, the MFR achieves the highest APP.

Electric vehicles (EVs) have emerged to be the future of transportation as the world observes its rising demand and usage across continents. However, currently, one of the biggest bottlenecks of EVs is the battery. Small batteries limit the EVs driving range, while big batteries are expensive and not environmentally friendly. One potential solution to this challenge is the deployment of charging roads, i.e., dynamic wireless charging systems installed under the roads that enable EVs to be charged while driving. In this thesis, we establish a framework using stochastic geometry to study the performance of deploying charging roads in metropolitan cities. We first present the course of actions that a driver may take when driving from a random source to a random destination, and then analyze the distribution of the distance to the nearest charging road and the probability that the trip passes through at least one charging road. These probability distributions assist not only urban planners and policy makers in designing deployment plans of dynamic wireless charging systems, but also drivers and automobile manufacturers in choosing the best driving routes given the road conditions and level of energy of EVs.

As the complexity of modern cellular networks continuously increases along with the evolution of technologies and the quick explosion of mobile data traffic, conventional large scale system level simulations and analytical tools become either too complicated or less tractable and accurate. Therefore, novel analytical models are actively pursued. In recent years, stochastic geometry models have been recognized as powerful tools to analyze the key performance metrics of cellular networks. In this dissertation, stochastic geometry based analytical models are developed to analyze the performance of some key technologies proposed for 5G mobile networks. Particularly, Device-to-Device (D2D) communication, Non-orthogonal multiple access (NOMA), and ultra-dense networks (UDNs) are investigated and analyzed by stochastic geometry models, more specifically, Poisson Point Process (PPP) models. D2D communication enables direct communication between mobile users in proximity to each other bypassing base station (BS). Embedding D2D communication into existing cellular networks brings many benefits such as improving spectrum efficiency, decreasing power energy consumption, and enabling novel location-based services. However, these benefits may not be fully exploited if the co-channel interference among D2D users and cellular users is not properly tackled. In this dissertation, various frequency reuse and power control schemes are proposed, aiming at mitigating the interference between D2D users and conventional cellular users. The performance gain of proposed schemes is analyzed on a system modeled by a 2-tier PPP and validated by numerical simulations. NOMA is a promising radio access technology for 5G cellular networks. Different with widely applied orthogonal multiple access (OMA) such as orthogonal frequency division multiple access (OFDMA) and single carrier frequency division multiple access (SC-FDMA), NOMA allows multiple users to use the same frequency/time resource and offers many advantages such as improving spectral efficiency, enhancing connectivity, providing higher cell-edge throughput, and reducing transmission latency. Although some initial performance analysis has been done on NOMA with single cell scenario, the system level performance of NOMA in a multi-cell scenario is not investigated in existing work. In this dissertation, analytical frameworks are developed to evaluate the performance of a wireless network with NOMA on both downlink and uplink. Distinguished from existing publications on NOMA, the framework developed in this dissertation is the first one that takes inter-cell interference into consideration. UDN is another key technology for 5G wireless networks to achieve high capacity and coverage. Due to the existence of line-of-sight (LoS)/non-line-of-sight (NLoS) propagation and bounded path loss behavior in UDN networks, the tractability of the original PPP model diminishes when analyzing the performance of UDNs. Therefore, a dominant BS (base station)-based approximation model is developed in this dissertation. By applying reasonable mathematical approximations, the tractability of the PPP model is preserved and the closed form solution can be derived. The numerical results demonstrate that the developed analytical model is accurate in a wide range of network densities. The analysis conducted in this dissertation demonstrates that stochastic geometry models can serve as powerful tools to analyze the performance of 5G technologies in a dense wireless network deployment. The frameworks developed in this dissertation provide general yet powerful analytical tools that can be readily extended to facilitate other research in wireless networks.

Mobile edge computing (MEC) can dramatically promote the compu- tation capability and prolong the lifetime of mobile users by offloading computation- intensive tasks to edge cloud. In this thesis, a spatial-random two-tier heterogeneous network (HetNet) is modelled to feature random node distribution, where the small- cell base stations (SBSs) and the macro base stations (MBSs) are cascaded with resource-limited servers and resource-unlimited servers, respectively. Only a certain type of application services and finite number of offloaded tasks can be cached and processed in the resource-limited edge server. For that setup, we investigate the per- formance of two offloading strategies corresponding to integrated access and backhaul (IAB)-enabled MEC networks and traditional cellular MEC networks. By using tools from stochastic geometry and queuing theory, we derive the average delay for the two different strategies, in order to better understand the influence of IAB on MEC networks. Simulations results are provided to verify the derived expressions and to reveal various system-level insights.

As we move towards the sixth generation (6G) of connectivity, satellites have been identified as an indispensable solution to bridge the digital divide. The satellites offer an extensive coverage footprint and can reach the most remote regions with high throughput, fueled by the large bandwidth available in higher frequency bands. As the low earth orbit (LEO) satellites are closer to the earth and therefore have lower latency, we could use a mega-constellation of LEO satellites to complement the terrestrial networks in 6G. However, the satellite and terrestrial networks may compete for the same spectrum band, thereby being a source of interference for each other. The mmWave bands have attracted the attention of LEO satellite networks and terrestrial mobile operators alike. Specifically, the 28-GHz mmWave band (27.5-29.5 GHz) is licensed to Fixed Satellite Services (FSS) for earth-to-satellite uplink transmissions, while the terrestrial networks will use it for downlink operation. The satellite networks are the primary users of the 28 GHz band, while it is also available for licensing to International Mobile Telecommunication (IMT) networks. In some countries, the 28 GHz band is also used for point-to-multipoint (PMP) wireless backhaul links. Therefore, in this work, we aim to understand the impact of the earth station uplink transmissions on the terrestrial users, viz., the cellular users, and the backhaul points, and suggest methods to facilitate the coexistence of these networks in the 28 GHz band through exclusion zones. The average data rate of the networks is derived through stochastic geometry, which results in expressions that are not closed-form. To optimize the data rates of the coexisting networks jointly, we first approximate the coverage probability expressions as closed-form sigmoid curves. This enables us to use gradient descent methods to determine the optimal radii of the exclusion zones.