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Ultra wideband (UWB) is a promising technology for short range and high-speed wireless communications such as home entertainment, wireless video downloading, wireless LAN, wireless USB and so on. This dissertation studied several important issues in the application of UWB technology and its contributions are summarized as follows. First, a 2-stage optimal UWB pulse shaping filter design procedure is proposed, which not only satisfies the FCC transmission spectral masks but also suppress the multiple access interference (MAI). The major advantages of the proposed joint optimization method are: (1) it has superior MAI suppression capability; (2) it can achieve the best system performance by optimizing transmitting and receiving filters jointly. Second, a pulse shaping optimizer is proposed to achieve the best received signal-to-noise ratio (SNR). Since the objective function of the SNR optimization has multiple maxima, genetic algorithms are adopted in this all-pass filter optimization. Third, a novel analytical method of assessing the narrowband performance degradation due to UWB interferences is proposed. This method models the UWB interferences as a composite signal of white Gaussian noise and jamming tones. Finally, a RAKE receiver simulation model under a realistic UWB channel is proposed and numerical results are presented. Overall, this dissertation investigates several important issues in the application of UWB technology, and provides some insights on the role of UWB technology in the evolving course of wireless communications. / Ph. D.

Aedes aegypti mosquitoes are the vectors of many significant arboviruses that cause tremendous social and economic impact. RNA interference (RNAi) plays a crucial role in the vector competence of mosquitoes and is often targeted in studies involving mosquito innate immunity, genetics-based vector control strategies, and the development of viral-resistant transgenic mosquitoes. In general, RNA interference is induced by double stranded RNA (dsRNA) and results in the inhibition of cognate gene expression. There are several different RNA interference pathways, with distinct functions and mechanisms. The micro RNA pathway is important for endogenous gene regulation and development. The endogenous small interfering RNA (endo-siRNA) pathway functions in gene regulation and protection of the genome from the deleterious effects of transposable elements. The exogenous siRNA (exosiRNA) pathway is a major contributor to mosquito innate immunity and vector competence by limiting viral replication during infection. Lastly, the piwi RNA (piRNA) pathway primarily functions in protecting the genome from the deleterious effects of transposable elements. While the structure and function of many genes involved in Drosophila RNAi have been characterized, the corresponding mosquito orthologs have only been peripherally described or remain unknown. Thus, the overall purpose of this study is to improve the understanding of mosquito RNAi mechanisms by identifying and analyzing genetic factors involved in the various pathways. This research especially focuses on characterizing and analyzing putative doubleiii stranded RNA binding proteins (dsRBPs) important to the function of the RNAi initiator and effector complexes. Two genes, r2d2 and r3d1 are orthologs of Drosophila genes known to have important roles in the RNAi initiator complex. A third member of the same family, which we refer to as extra loquacious (exloqs), appears to have no known orthologs outside of the Aedes genus. Structural characterization of these genes included identification of single nucleotide polymorphisms (SNPs), novel exons and alternative splice variants. RT-PCR assays were utilized to examine differential expression of all three genes in specific tissues and developmental stages. Sub-cellular fractionation assays enabled intracellular localization of the RNAi proteins within Ae. aegypti cells. Co-immunoprecipitation of tagged dsRBPs revealed protein-protein interactions between specific dsRBPs and known RNAi factors. In addition, an exo-siRNA sensor was designed and tested in-vivo and in-vitro with the purpose of facilitating the identification of novel genetic factors involved in this anti-viral pathway. Lastly, TALENbased gene disruption was successfully employed to knockout the exloqs gene in Ae. aegypti mosquitoes, enabling further analysis into the function of this gene. The research described in this document provides further insight into mosquito innate immunity and gene regulation, which is important to the advancement of genetics-based vector control strategies. / Ph. D.

This works systematically presents various strategies to reduce both differential mode (DM) and common mode (CM) noise using a passive filter in a dc-fed motor drive. Following a standard approach a baseline filter is first designed to be used as reference to understand and compare the available filter topologies. Furthermore, it is used to analyze the grounding scheme of EMI filter and more specifically provide guidelines to ground single or multi stages filter. Finally, the baseline filter is investigated to recognize the possible solutions to minimize the size of the whole filter. It turns out that the CM choke and DM capacitors are the two main downsides to achieve a small EMI filter. Therefore, ideas are proposed to improve the CM choke by using other type of material such as nano crystalline core, different winding technique and new integrated method. A material comparison study is made between the common ferrite core and the nano crystalline core. Its advantages (high permeability and saturation flux density) and drawback (huge permeability drop) are analyzed thought multitudes of small and large signals tests. A novel integrated filter structure is addressed that maximizes the window area of the ferrite core and increases its leakage inductance by integrating both CM and DM inductances on the same core. Small- and large-signal experiments are conducted to verify the validity of the structure showing an effective size reduction and a good improvement at low and high frequencies. To conclude, a final filter version is proposed that reduce the volume of the baseline filter by three improve the performances in power tests. / Master of Science

The demand for mobile wireless network resources is constantly on the rise, pushing for new communication technologies that are able to support unprecedented rates. In this thesis we address the issue by considering advanced interference management techniques to exploit the available resources more efficiently under relaxed channel state information (CSI) assumptions. While the initial studies focus on current half-duplex (HD) technology, we then move on to full-duplex (FD) communication due to its inherent potential to improve spectral efficiency. Work in this thesis is divided into four main parts as follows. In the first part, we focus on the two-cell two-user-per-cell interference broadcast channel (IBC) and consider the use of topological interference management (TIM) to manage inter-cell interference in an alternating connectivity scenario. Within this context we derive novel outer bounds on the achievable degrees of freedom (DoF) for different system configurations, namely, single-input single-output (SISO), multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) systems. Additionally, we propose new transmission schemes based on joint coding across states that exploit global topological information at the transmitter to increase achievable DoF. Results show that when a single state has a probability of occurrence equal to one, the derived bounds are tight with up to a twofold increase in achievable DoF for the best case scenario. Additionally, when all alternating connectivity states are equiprobable: the SISO system gains 11/16 DoF, achieving 96:4% of the derived outer bound; while the MISO/MIMO scenario has a gain of 1/2 DoF, achieving the outer bound itself. In the second part, we consider a general G-cell K-user-per-cell MIMO IBC and analyse the performance of linear interference alignment (IA) under imperfect CSI. Having imperfect channel knowledge impacts the effectiveness of the IA beamformers, and leads to a significant amount of residual leakage interference. Understanding the extent of this impact is a fundamental step towards obtaining a performance characterisation that is more relevant to practical scenarios. The CSI error model used is highly versatile, allowing the error to be treated either as a function of the signal-to-noise ratio (SNR) or as independent of it. Based on this error model, we derive a novel upper bound on the asymptotic mean sum rate loss and quantify the DoF loss due to imperfect CSI. Furthermore, we propose a new version of the maximum signal-to-interference plus noise ratio (Max-SINR) algorithm which takes into account statistical knowledge of the CSI error in order to improve performance over the naive counterpart in the presence of CSI mismatch. In the third part, we shift our attention to FD systems and consider weighted sum rate (WSR) maximisation for multi-user multi-cell networks where FD base-stations (BSs) communicate with HD downlink (DL) and uplink (UL) users. Since WSR problems are non-convex we transform them into weighted minimum mean squared error (WMMSE) ones that are proven to converge. Our analysis is first carried out for perfect CSI and then expanded to cater for imperfect CSI under two types of error models, namely, a norm-bounded error model and a stochastic error model. Additionally, we propose an algorithm that maximises the total DL rate subject to each UL user achieving a desired target rate. Results show that the use of FD BSs provides significant gains in achievable rate over the use of HD BSs, with a gain of 1:92 for the best case scenario under perfect CSI. They also demonstrate the robust performance of the imperfect CSI designs, and confirm that FD outperforms HD even under CSI mismatch conditions. Finally, the fourth part considers the use of linear IA to manage interference in a multi-user multi-cell network with FD BSs and HD users under imperfect CSI. The number of interference links present in such a system is considerably greater than that present in the HD network counterpart; thus, understanding the impact of residual leakage interference on performance is even more important for FD enabled networks. Using the same generalised CSI error model from the second part, we study the performance of IA by characterising the sum rate and DoF losses incurred due to imperfect CSI. Additionally, we propose two novel IA algorithms applicable to this network; the first one is based on minimising the mean squared error (MMSE), while the second is based on Max-SINR. The proposed algorithms exploit statistical knowledge of the CSI error variance in order to improve performance. Moreover, they are shown to be equivalent under certain conditions, even though the MMSE based one has lower computational complexity. Furthermore for the multi-cell case, we also derive the proper condition for IA feasibility.

This thesis deals with an experimental research of the surface plasmon polaritons (SPPs) using Scanning Near-field Optical Microscopy (SNOM). The first chapter provides theoretical background and a description of most of the physical phenomena and relevant dependencies studied in this work. These dependencies include the dependence of the resulting SPP image on homogeneity, polarization, wavelength and phase of the illumination, on the geometry of the interference structures and on the tilt of the sample with respect to the illumination. Further, this work presents a new experimental method which, using the numerical simulations or SNOM measurements, allows to estimate the sensitivity of SNOM probe to detect the individual electric intensity components of the near-field. At the end of the thesis, the work presents a new microscopic technique which enables a 3D quantitative imaging of phase distribution above the plasmonic metasurfaces.

<div> Interference management is necessary to meet the growth in demand for wireless data services. The problem was studied in previous work by assuming a fixed channel connectivity model, while network topologies tend to change frequently in practice. </div><div><br></div><div>The associations between cell edge mobile terminals and base stations in a wireless interference network that is backed by cooperative communication schemes is investigated and association decisions are identified that are information-theoretically optimal when taking the uplink-downlink average. Then, linear wireless networks are evaluated from a statistical point of view, where the associations between base stations and mobile terminals are fixed and channel fluctuations exist due to shadow fading. Moreover, the considered fading model is formed by having links in the wireless network, each subject independently to erasure with a known probability. </div><div><br></div><div>Throughout the information theoretic analysis, it is assumed that the network topology is known to the cooperating transmitting nodes. This assumption may not hold in practical wireless networks, particularly Ad-Hoc ones, where decentralized mobile nodes form a temporary network. Further, communication in many next generation networks, including cellular, is envisioned to take place over different wireless technologies, similar to the co-existence of Bluetooth, ZigBee, and WiFi in the 2.4 GHz ISM-Band. The competition of these wireless technologies for scarce spectrum resources confines their coexistence. It is hence elementary for collaborative interference management strategies to identify the channel type and index of a wireless signal, that is received, to promote intelligent use of available frequency bands. It is shown that deep learning based approaches can be used to identify interference between the wireless technologies of the 2.4 GHz ISM-Band effectively, which is compulsory for identifying the channel topology. The value of using deep neural network architectures such as CNN, CLDNN, LSTM, ResNet and DenseNet for this problem of Wireless Channel Identification is investigated. Here, the major focus is on minimizing the time, that takes for training, and keeping a high classification accuracy of the different network architectures through band and training SNR selection, Principal Component Analysis (PCA) and different sub-Nyquist sampling techniques. </div><div>Finally, a number theoretic approach for fast discovery of the network topology is proposed. More precisely, partial results on the simulation of the message passing model are utilized to present a model for discovering the network topology. Specifically, the minimum number of communication rounds needed to discover the network topology is examined. Here, a single-hop network is considered that is restricted to interference-avoidance, i.e., a message is successfully delivered if and only if the transmitting node is the only active transmitter connected to its receiving node. Then, the interference avoidance restriction is relaxed by assuming that receivers can eliminate interference emanating from already discovered transmitters. Finally, it is explored how the network size and the number of interfering transmitters per user adjust the sum of observations.</div><div><br></div>

Interference is a fundamental problem in wireless networks. An effective solution to this problem usually calls for a cross-layer approach. Although there exist a large volume of works on interference management techniques in the literature, most of them are limited to signal processing at the physical (PHY) layer or information-theoretic exploitation. Studies of advanced interference techniques from a cross-layer optimization perspective remain limited, especially involving multi-hop wireless networks. This dissertation aims at filling this gap by offering a comprehensive investigation of three interference techniques: interference cancellation (IC), interference alignment (IA), and interference neutralization (IN). This dissertation consists of three parts: the first part studies IC in distributed multi-hop multiple-input multiple-output (MIMO) networks; the second part studies IA in multi-hop networks, cellular networks, and underwater acoustic (UWA) networks; and the third part focuses on IN in multi-hop single-antenna networks. While each part makes a step towards advancing an interference technique, they collectively constitute a body of work on interference management in the networking research community. Results in this dissertation not only advance network-level understanding of the three interference management techniques, but also offer insights and guidance on how these techniques may be incorporated in upper-layer protocol design. In the first part, we study IC in multi-hop MIMO networks where resource allocation is achieved through neighboring node coordination and local information exchange. Based on a well-established degree-of-freedom (DoF) MIMO model, we develop a distributed DoF scheduling algorithm with the objective of maximizing network-level throughput while guaranteeing solution feasibility at the PHY layer. The proposed algorithm accomplishes a number of beneficial features, including polynomial-time complexity, amenability to local implementation, a guarantee of feasibility at the PHY layer, and competitive throughput performance. Our results offer a definitive ``yes'' answer to the question --- Can the node-ordering DoF model be deployed in a distributed multi-hop MIMO network? In particular, we show that the essence of the DoF model --- a global node ordering, can be implicitly achieved via local operations, albeit it is invisible to individual node. In the second part, we investigate IA in various complex wireless networks from a networking perspective. Specifically, we study IA in three different domains: spatial domain, spectral domain, and temporal domain. In the spatial domain, we study IA for multi-hop MIMO networks. We derive a set of simple constraints to characterize the IA capability at the PHY layer. We prove that as long as the set of simple constraints are satisfied, there exists a feasible IA scheme (i.e., precoding and decoding vectors) at the PHY layer so that the data streams on each link can be transported free of interference. Therefore, instead of dealing with the complex design of precoding and decoding vectors, our IA constraints only require simple algebraic addition/subtraction operations. Such simplicity allows us to study network-level IA problems without being distracted by the tedious details in signal design at the PHY layer. Based on these IA constraints, we develop an optimization framework for unicast and multicast communications. In the spectral domain, we study IA in OFDM-based cellular networks. Different from spatial IA, spectral IA is achieved by mapping data streams onto a set of frequency bands/subcarriers (rather than a set of antenna elements). For the uplink, we derive a set of simple IA constraints to characterize a feasible DoF region for a cellular network. We show how to construct precoding and decoding vectors at the PHY layer so that each data stream can be transported free of interference. Based on the set of IA constraints, we study a user throughput maximization problem and show the throughput improvement over two other schemes via numerical results. For the downlink, we find that we can exploit the uplink IA constraints to the downlink case simply by reversing the roles of user and base station. Further, the downlink user throughput maximization problem has the exactly same formulation as the uplink problem and thus can be solved in the exactly same way. In the temporal domain, we study IA for UWA networks. A fundamental issue in UWA networks is large propagation delays due to slow signal speed in water medium. But temporal IA has the potential to turn the adverse effect of large propagation delays into something beneficial. We propose a temporal IA scheme based on propagation delays, nicknamed PD-IA, for multi-hop UWA networks. We first derive a set of PD-IA constraints to guarantee PD-IA feasibility at the PHY layer. Then we develop a distributed PD-IA scheduling algorithm, called Shark-IA, to maximally overlap interference in a multi-hop UWA network. We show that PD-IA can turn the adverse propagation delays to throughput improvement in multi-hop UWA networks. In the third part, we study IN for multi-hop single-antenna networks with full cooperation among the nodes. The fundamental problem here is node selection for IN in a multi-hop network environment. We first establish an IN reference model to characterize the IN capability at the PHY layer. Based on this reference model, we develop a set of constraints that can be used to quickly determine whether a subset of links can be active simultaneously. By identifying each eligible neutralization node as a neut, we study IN in a multi-hop network with a set of sessions and derive the necessary constraints to characterize neut selection, IN, and scheduling. These constraints allow us to study IN problems from a networking perspective but without the need of getting into signal design issues at the PHY layer. By applying our IN model and constraints to study a throughput maximization problem, we show that the use of IN can generally increase network throughput. In particular, throughput gain is most significant when there is a sufficient number of neuts that can be used for IN. In summary, this dissertation offers a comprehensive investigation of three interference management techniques (IC, IA, and IN) from a networking perspective. Theoretical and algorithmic contributions of this dissertation encompass characterization of interference exploitation capabilities at the PHY layer, derivation of tractable interference models, development of feasibility proof for each interference model, formulation of throughput maximization problems, design of distributed IC and PD-IA scheduling algorithms, and development of near-optimal solutions with a performance guarantee. The results in this dissertation offer network-level understanding of the three interference management techniques and lay the groundwork for future research on interference management in wireless networks. / Ph. D.