In this thesis, we construct a mathematical model for Sectorized FFR Networks (SFN). In SFN, frequency allocation adopts FFR (Fractional Frequency Reuse), which divides the frequency into two parts: the super group (Sup-G) and the regular group (Reg-G). Since the frequency allocations of Sup-G and sectors overlaps each other, and the same frequency band is used by two Sup-G in two different BS, when the radius of Sup-G is too large, interferences will occur among the adjacent BS. In our mathematical model, given different environmental parameters (number of sector, number of MS, strength of power), we can compute the system capacity by varying the radius of Sup-G and the various environmental parameters. In practical applications, since the number of MS becomes smaller in the cellular edge and it increases rapidly in the cellular center, Gaussian distribution is more adequate to model the distribution of MS. Thus, in the calculation of interference, we take the integration of the path loss multiplied by the transmission power and the MS density. Finally, through the SINR and Shannon Capacity formula, we can derive the overall system capacity. From the mathematical model, we can achieve a ratio of Sup-G radius and cellular radius. With this radius ratio, an MS can have about the same capacity regardless of the position in the FFR network. Otherwise, an MS may get very different capacity when it moves to the cellular edge or sometimes it appears in the cellular center. Additionally, from the mathematical model, we can analyze the interferences and system capacity for different numbers of sectors.

Doctor of Philosophy / Genetics Interdepartmental Program / Revathi Govind / Clostridium difficile is a gram-positive anaerobic, motile, spore-forming opportunistic bacterium. It is a nosocomial pathogen, and the symptoms of C. difficile infection (CDI) range from mild diarrhea to life-threatening pseudomembranous colitis and toxic megacolon. Antibiotic use is the primary risk factor for the development of CDI as it disrupts the healthy protective gut flora which enables C. difficile to colonize and establish in the colon. C. difficile damages the host tissue by secreting toxins and disseminates in the environment by forming spores. The two-major toxin-encoding genes, tcdA, and tcdB are located within a 19.6 kb pathogenicity locus (PaLoc), which also includes the gene encoding an RNA polymerase sigma factor TcdR, that is essential for toxin gene expression. We created a site-directed mutation in tcdR in the epidemic-type C. difficile R20291 strain and found that disruption of tcdR affected sporulation in addition to toxin production. Spores of the tcdR mutant were more heat- sensitive and required nearly three-fold higher taurocholate to germinate when compared to the wild-type (WT). Transmission Electron Microscopic analysis of the tcdR mutant spores also revealed a weakly assembled exosporium. Consistent with our phenotypic assays, our comparative transcriptome analysis also showed significant downregulation of sporulation genes in the tcdR mutant when compared to the WT strain. Our findings on tcdR suggest that the regulatory networks of toxin production and sporulation in C. difficile R20291 strain are interlinked with each other. Transcriptome analysis revealed the sin operon to be significantly downregulated in the tcdR mutant which made us hypothesize the link between sin operon regulation and sporulation. The sin locus coding SinR (113 aa) and SinI (57 aa) is responsible for sporulation inhibition in B. subtilis. SinR in B. subtilis mainly acts as a repressor of its target genes to control sporulation, biofilm formation, and autolysis. SinI is an inhibitor of SinR, and SinI/SinR interaction determines whether or not the SinR can inhibit target gene expression. The C. difficile genome carries two sinR homologs in the operon, and we named it as sinR and sinR’, coding for SinR (112 aa) and SinR’ (105 aa), respectively. To identify the regulation of sin on sporulation, we created a site-directed mutation in the sin locus in two different C. difficile strains R20291 and JIR8094. Comparative transcriptome analysis of the sinRR’ mutants revealed their pleiotropic roles in controlling several essential pathways including sporulation, toxin production, and motility (STM) in C. difficile. We performed several genetic and biochemical experiments, to prove that SinR regulates transcription of crucial regulators in STM pathways, which includes sigD, spo0A, and codY. Unlike B. subtilis, SinR’ acts as an antagonist of SinR and SinR’/SinR determines SinR activity. Our in vivo experiment using hamster model also demonstrated the importance of sin locus for successful C. difficile colonization. Our findings above reveal that sin locus acts as a central link that regulates essential pathways including sporulation, toxin production, and motility, which are critical for C. difficile pathogenesis. The final section of this dissertation analyzes a variant codY gene in the epidemic C. difficile R20291 strain. In this strain the CodY, a global nutrient sensor-regulator carry a missense mutation where the 146th tyrosine residue is replaced with asparagine (CodY[superscript Y146N]). Our preliminary study with the mutated CodY[superscript Y146N] suggested its differential role in its regulatory activity. Further analysis of CodY[superscript Y146N] might give some possible clues behind the hypervirulent nature of epidemic R20291 strain. Taken together, studies performed on both tcdR and sinR mutants reveal a significant amount of crosstalk occurring between the powerful regulators of STM pathways under the directionality of TcdR and SinR in determining their ultimate cell fate. Our findings on CodY[superscript Y146N] suggest how the bacteria could switch to a hypervirulence mode by manipulating one of its vital regulators like CodY.

Ericsson Brasil / The International Telecommunications Union (ITU) established through the International Mobile Telecommunications (IMT)-Advanced a set of requirements for high performance of 4th Generation (4G) communication systems and, with the aim of meeting such requirements, 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) is considering a set of enhancements, referred to as LTE-Advanced. In the LTE-Advanced context, Coordinated Multi-Point (CoMP) communication appears as a promising technology to boost system throughput and to allow for an efficient Radio Resource Allocation (RRA). CoMP systems promise very high performance in terms of spectral efficiency and coverage benefits when perfect Channel State Information (CSI) is available at the transmitter. However, perfect CSI is difficult to obtain in CoMP systems due to an increased number of channel parameters to be estimated at the receiver and to be fed back to the transmitter. So, the performance of such systems is compromised when the CSI is not perfectly known during CoMP processing, which is an important problem to be addressed. Space Division Multiple Access (SDMA) grouping algorithms are usually employed in order to find a suitable set of users for spatial multiplexing. The largest SDMA group is not always the best group in a given data transmission such that higher gains might be achieved by dynamically adjusting the SDMA group size. Besides, algorithms that balance the Signal to Interference-plus-Noise Ratio (SINR) among different links might ensure a certain level of link quality and so provide a more reliable communication for the scheduled users. This master thesis provides system-level analyses for RRA algorithms that exploit coordination in the downlink of CoMP systems to implement adaptive resource reuse and so improve system throughput. Herein, RRA strategies which consider dynamic SDMA grouping, joint precoding and power allocation for SINR balancing are studied in CoMP systems assuming imperfect CSI in order to obtain a better approximation with regard to the real-world implementations. It is shown through system-level analyses that quite high throughput gains are achieved through intelligent RRA. In conclusion, the results show that Sequential Removal Algorithms (SRAs) and SINR balancing provide system spectral efficiency gains. However, a critical degradation on the performance of these RRA strategies due to imperfect CSI is also shown. / A UniÃo Internacional para TelecomunicaÃÃes (ITU) estabeleceu atravÃs da iniciativa para o Sistema AvanÃado Internacional de TelecomunicaÃÃes MÃveis (IMT-Advanced), um conjunto de requisitos de alto desempenho para os sistemas de comunicaÃÃo de quarta geraÃÃo (4G) e, com o objetivo de atender tais requisitos, a EvoluÃÃo de Longo Prazo (LTE) do Projeto de Parceria para a Terceira GeraÃÃo (3GPP) està considerando um conjunto de melhorias, referidas como LTE-AvanÃado. No contexto do LTE-AvanÃado, a comunicaÃÃo multi-ponto coordenada (CoMP) aparece como uma tecnologia promissora para aumentar a vazÃo do sistema e permitir uma AlocaÃÃo de Recursos de RÃdio (RRA) eficiente. Os sistemas CoMP prometem alto desempenho em termos de eficiÃncia espectral e benefÃcios de cobertura quando a InformaÃÃo do Estado do Canal (CSI) perfeita està disponÃvel no transmissor. No entanto, CSI perfeita à difÃcil de se obter em sistemas CoMP devido a um alto nÃmero de parÃmetros de canal a serem estimados no receptor e enviados para o transmissor. Assim, o desempenho de tais sistemas à comprometido quando a CSI nÃo à perfeitamente conhecida durante o processamento CoMP tal que esse à um problema importante a ser abordado. Algoritmos de agrupamento para MÃltiplo Acesso por DivisÃo no EspaÃo (SDMA) geralmente sÃo utilizados a fim de encontrar um conjunto adequado de usuÃrios para multiplexaÃÃo espacial. O maior grupo SDMA nem sempre à o melhor grupo em uma transmissÃo de dados tal que maiores ganhos podem ser obtidos ajustando dinamicamente o tamanho do grupo SDMA. AlÃm disso, os algoritmos que balanceiam a RazÃo Sinal-InterferÃncia mais RuÃdo (SINR) entre diferentes canais podem garantir um certo nÃvel de qualidade de canal e assim proporcionar uma comunicaÃÃo mais confiÃvel para os usuÃrios agrupados. Esta dissertaÃÃo de mestrado fornece anÃlises em nÃvel sistÃmico para algoritmos de RRA que exploram a coordenaÃÃo no enlace direto de sistemas CoMP para implementar reuso adaptativo de recursos e assim melhorar o desempenho do sistema. SÃo estudadas aqui estratÃgias de RRA em sistemas CoMP que consideram agrupamento SDMA dinÃmico, precodificaÃÃo e alocaÃÃo de potÃncia conjuntas para balanceamento de SINR, sendo assumida CSI imperfeita a fim de conseguir maior aproximaÃÃo com relaÃÃo Ãs implementaÃÃs em cenÃrios reais. à mostrado atravÃs de anÃlises em nÃvel sistÃmico que ganhos de vazÃo bastante altos sÃo alcanÃados atravÃs de RRA inteligente. Em conclusÃo, os resultados mostram que Algoritmos de RemoÃÃo Sequencial (SRAs) e de balanceamento de SINR proporcionam ganhos de eficiÃncia espectral do sistema. No entanto, à tambÃm mostrada uma degradaÃÃo crÃtica no desempenho dessas estratÃgias de RRA devido à CSI imperfeita.

Strong demand for wireless communications encourages academic research centres and industrial electronics and communication companies to keep improving the performance, increase the speed, extend the coverage area and enlarge the baud rate and capacity. LTE (Long Term Evolution) and WiMAX (the Worldwide Interoperability Microwave Access) are recent solutions for most wireless technologies. LTE and WiMAX coverage range are one of the important factors that affect the quality of broadband access services and mobile cellular systems in wireless communication. Predicting and evaluating the path loss is essential in planning and designing cellular mobile systems. This thesis presents a comprehensive study of path loss on LTE and mobile WiMAX to achieve large throughputs and wide coverage at the Cell-edge. The thesis introduces, analyzes and compares the path loss values, based on LTE and WiMAX standard at one carrier frequency, namely 3.5GHz and a variation of distances in the range of 1 to 50 km, in flat rural, suburban and urban environments. The thesis discusses and implements the Okumura, Hata, Cost-231, Ericsson, Erceg, Walfish, Ecc-33, Lee and the simplified free space path loss models. The objectives of path loss evaluation results are to calculate the link budget, the power outage and the base station cell coverage area for mobile cellular systems. A femtocell (FMC) is a low cost low power cellular home base station, operating in licensed spectrum. Because of the requirement for high data rates and improved coverage indoors, FMC provides a solution to these requirements. FMC is deployed mainly indoors and sometimes outdoors at the cell-edge to increase the area of coverage, capacity and in order to enhance the received signal in the user’s premises. The thesis presents the interference, SINR and the probability of connection for the downlink with different numbers of FMCs based on LTE and WiMAX OFDMA. Moreover, comparisons of interference, SINR and probability of connection for three different numbers of FMCs and for three different indoor areas are presented. In addition, a comparison for the probability of connection with various threshold values and numbers of FMCs is simulated and presented in 3-D. The probability of connection for a varied number of FMCs is a guide study to find the appropriate number of FMCs that could serve a specific indoor area and the proper number of UEs in the specified area. The thesis also presents the interference, SINR and the probability of connection at the uplink for a user equipment device (UE) to an FMC with varied number of UEs based on LTE and WiMAX OFDMA. Moreover, comparisons of the interference, SINR and probability of connection for three different areas at the uplink are presented. Therefore, analyzing probability of connection with varied number of UEs is a worthy study in order to identify the appropriate number of UEs that could be served by a specific number of FMCs at a specific indoor location. The thesis presents and investigates the capacity of MIMO with the presence of FMCs to perform cancellation of co-channel interference. The research introduces algorithms to calculate the capacity of MIMO with the presence of FMCs by two models. The simulation results show that the capacity equations of model-2 give better results than the capacity equations of model-1. Therefore, model-2 is used for the interference cancellation of MIMO in the presence of MIMO. Interference cancellation is performed at the downlink when the signal is transmitted from FMC to UE by mitigating and cancelling the interference which comes from the neighbouring FMCs to the target UE. The thesis introduces, explains and applies a novel algorithm to calculate the capacity of MIMO at the presence of FMCs with interference cancellation by these channel equalizers ZF, MMSE, VBLAST ZF, VBLAST MMSE and VBLAST OFDM MMSE.

Currently, data size that we have to deal with is growing bigger and bigger. This fact implies that the computing time and computing power for dealing with the data is demanded. A way to circumvent the difficulty is as follows: Divide the data into several small blocks and then process these small blocks by several computers. Therefore, we need a tool for the decomposition-coordinated procedure. Alternating direction method of multipliers (ADMM) is a powerful algorithm for the mentioned purpose and has widely used in distributed optimizations. With ADMM algorithm, a big global optimization problem can be decomposed into several small local optimization problems. ADMM algorithm has been used in several recent distributed systems such as cloud systems and distributed antenna systems. In this thesis, we aim to apply the ADMM in a distributed antenna system. For the uplink setting, we develop a distributed demodulation algorithm, where multiple base stations collaborate with each other for data detection. On the other hand, for the downlink setting, we develop a distributed beamforming design algorithm, where multiple base stations collaborate to form a beamforming for mitigating the inter-cell interference. Finally, simulations are conducted to verify the efficiency of our designs.

Alongside the ever increasing traffic demand, the fifth generation (5G) cellular network architecture is being proposed to provide better quality of service, increased data rate, decreased latency, and increased capacity. Without any doubt, the 5G cellular network will comprise of ultra-dense networks and multiple input multiple output technologies. This will make the current centralised solutions impractical due to increased complexity. Moreover, the amount of coordination information that needs to be transported over the backhaul links will be increased. Distributed or decentralised solutions are promising to provide better alternatives. This thesis proposes new distributed algorithms for wireless networks which aim to reduce the amount of system overheads in the backhaul links and the system complexity. The analysis of conflicts amongst transmitters, and resource allocation are conducted via the use of game theory, convex optimisation, and auction theory. Firstly, game-theoretic model is used to analyse a mixed quality of service (QoS) strategic non-cooperative game (SNG), for a two-user multiple-input single-output (MISO) interference channel. The players are considered to have different objectives. Following this, the mixed QoS SNG is extended to a multicell multiuser network in terms of signal-to-interference-and-noise ratio (SINR) requirement. In the multicell multiuser setting, each transmitter is assumed to be serving real time users (RTUs) and non-real time users (NRTUs), simultaneously. A novel mixed QoS SNG algorithm is proposed, with its operating point identified as the Nash equilibrium-mixed QoS (NE-mixed QoS). Nash, Kalai-Smorodinsky, and Egalitarian bargain solutions are then proposed to improve the performance of the NE-mixed QoS. The performance of the bargain solutions are observed to be comparable to the centralised solutions. Secondly, user offloading and user association problems are addressed for small cells using auction theory. The main base station wishes to offload some of its users to privately owned small cell access points. A novel bid-wait-auction (BWA) algorithm, which allows single-item bidding at each auction round, is designed to decompose the combinatorial mathematical nature of the problem. An analysis on the existence and uniqueness of the dominant strategy equilibrium is conducted. The BWA is then used to form the forward BWA (FBWA) and the backward BWA (BBWA). It is observed that the BBWA allows more users to be admitted as compared to the FBWA. Finally, simultaneous multiple-round ascending auction (SMRA), altered SMRA (ASMRA), sequential combinatorial auction with item bidding (SCAIB), and repetitive combinatorial auction with item bidding (RCAIB) algorithms are proposed to perform user offloading and user association for small cells. These algorithms are able to allow bundle bidding. It is then proven that, truthful bidding is individually rational and leads to Walrasian equilibrium. The performance of the proposed auction based algorithms is evaluated. It is observed that the proposed algorithms match the performance of the centralised solutions when the guest users have low target rates. The SCAIB algorithm is shown to be the most preferred as it provides high admission rate and competitive revenue to the bidders.

No description available.

Classical adaptive signal processors typically utilize assumptions in their derivation. The presence of adequate Gaussian and independent and identically distributed (i.i.d.) input data are central among such assumptions. However, classical processors have a tendency to suffer a degradation in performance when assumptions like these are violated. Worse yet, such degradation is not guaranteed to be proportional to the level of deviation from the assumptions. This dissertation proposes new signal processing algorithms based on aspects of modern robustness theory, including methods to enable adaptivity of presently non-adaptive robust approaches. The contributions presented are the result of research performed jointly in two disciplines, namely robustness theory and adaptive signal processing. This joint consideration of robustness and adaptivity enables improved performance in assumption-violating scenarios—scenarios in which classical adaptive signal processors fail. Three contributions are central to this dissertation. First, a new adaptive diagnostic tool for high-dimension data is developed and shown robust in problematic contamination. Second, a robust data-pre-whitening method is presented based on the new diagnostic tool. Finally, a new suppression-based robust estimator is developed for use with complex-valued adaptive signal processing data. To exercise the proposals and compare their performance to state- of-the art methods, data sets commonly used in statistics as well as Space-Time Adaptive Processing (STAP) radar data, both real and simulated, are processed, and performance is subsequently computed and displayed. The new algorithms are shown to outperform their state-of-the-art counterparts from both a signal-to-interference plus noise ratio (SINR) convergence rate and target detection perspective. / Ph. D.

A fundamental problem in multi-hop wireless networks is to estimate their throughout capacity. The problem can be informally stated as follows: given a multi-hop wireless network and a set of source destination pairs, determine the maximum rate r at which data can be transmitted between each source destination pair. Estimating the capacity of a multi-hop wireless network is practically useful --- it yields insights into the fundamental performance limits of the wireless network and at the same time aids the development of protocols that can utilize the network close to this limit. A goal of this dissertation is to develop rigorous mathematical foundations to compute the capacity of any given multi-hop wireless network with known source-destination pairs. An important factor that affects the capacity of multi-hop wireless networks is radio interference. As a result, researchers have proposed increasingly realistic interference models that aim to capture the physical characteristics of radio signals. Some of the commonly used simple models that capture radio interference are based on geometric disk-graphs. The simplicity of these models facilitate the development of provable and often conceptually simple methods for estimating the capacity of wireless networks. A potential weakness of this class of models is that they oversimplify the physical process by assuming that the signal ends abruptly at the boundary of a geometric region (a disk for omni-directional antennas). A more sophisticated interference model is the physical interference model, also known as the Signal to Interference Plus Noise Ratio (SINR) model. This model is more realistic than disk-graph models as it captures the effects of signal fading and ambient noise. This work considers both disk-graph and SINR interference models. In addition to radio interference, the throughput capacity of a multi-hop wireless network also depends on other factors, including the specific paths selected to route the packets between the source destination pairs (routing), the time at which packets are transmitted (scheduling), the power with which nodes transmit (power control) and the rate at which packets are injected (rate control). In this dissertation, we consider three different problems related to estimating network capacity. We propose an algorithmic approach for solving these problems. We first consider the problem of maximizing throughput with the SINR interference model by jointly considering the effects of routing and scheduling constraints. Second, we consider the problem of maximizing throughput by performing adaptive power control, scheduling and routing for disk-graph interference models. Finally, we examine the problem of minimizing end-to-end latency by performing joint routing, scheduling and power control using the SINR interference model. Recent results have shown that traditional layered networking principles lead to inefficient utilization of resources in multi-hop wireless networks. Motivated by these observations, recent papers have begun investigating cross-layer design approaches. Although our work does not develop new cross-layered protocols, it yields new insights that could contribute to the development of such protocols in the future. Our approach for solving these multi-objective optimization problems is based on combining mathematical programming with randomized rounding to obtain polynomial time approximation algorithms with provable worst case performance ratios. For the problems considered in this work, our results provide the best analytical performance guarantees currently known in the literature. We complement our rigorous theoretical and algorithmic analysis with simulation-based experimental analysis. Our experimental results help us understand the limitations of our approach and assist in identifying certain parameters for improving the performance of our techniques. / Ph. D.

Le relayage cognitif multiple-input multiple-output (MIMO) hérite l’efficacité spectrale de la radiocognitive et les systèmes de relayage MIMO, apportant ainsi des gains prometteurs en termes de débit dedonnées et de fiabilité pour les futures communications sans fil et mobiles. Dans cette thèse, nous concevons et évaluons des schémas pratiques d’émetteurs et de récepteurs pour des systèmes de relayage MIMO cognitifs qui peuvent être mis en oeuvre à moindre coût. Tout d'abord, nous réduisons l'affaiblissement du débit du mode half-duplex du relayage MIMO amplify-and-forward non-orthogonale(NAF) large bande avec demande de répétition automatique (ARQ). Différemment des travaux de recherche existants, le protocole de relayage proposé ne nécessite que la durée de transmission d’un seul paquet sur des canaux sélectifs en fréquence. De plus, nous proposons une conception de réception itérative à complexité réduite pour cette classe de protocoles, entraînant ainsi une amélioration significative des performances de transmission de bout-en-bout. Deuxièmement, nous nous concentrons sur les systèmes de relayage cognitive de partage du spectre single-input multiple-output (SIMO) et évaluons l’impact des contraintes d’interférence instantanée et statistique sur la qualité de leur probabilité de coupure. Nos résultats révèlent que l’imposition d’une contrainte statistique sur la puissance d’émission du système secondaire est plus favorable que son adversaire consommatrice de spectre. Troisièmement, nous capitalisons sur notre deuxième contribution pour étudier les systèmes de relayage MIMO decode-and-forward (DF) cognitifs utilisant la sélection d'antenne à l’émission (TAS) ainsi que le maximum-ratio combining (MRC) à la réception. Basés sur la maximisation du rapport signal-sur-bruit (SNR) ou du rapport signal-sur-interférence-plus-bruit (SINR), nos résultats de probabilité de coupure nouvellement dérivés pour les deux stratégies proposées de TAS démontre l’optimalité du système de sélection d’antenne basé sur le SINR par rapport aux effets néfastes d’interférence mutuelle dans les systèmes de relayage MIMO DF cognitifs. / Cognitive multiple-input multiple-output (MIMO) relaying inherits the spectrum usage efficiency from both cognitive radio and MIMO relay systems, thereby bearing promising gains in terms of data rate and reliability for future wireless and mobile communications. In this dissertation, we design and evaluate practical transmitter and receiver schemes for cognitive MIMO relay systems that can readily be implemented at a lower cost. First, we reduce the multiplexing loss due the half-duplex operation in non orthogonal amplify-and-forward (NAF) MIMO relay broadband transmissions with automatic repeat request(ARQ). Different from existing research works, the proposed relaying protocol requires only one packet duration to operate over frequency-selective block-fading relay channels. Further, we propose a low complexityiterative receiver design for this class of protocols which results in significant enhancement of the end-to-end transmission performance. Second, we focus on cognitive underlay single-input multiple-output (SIMO) relay systems and evaluate the impact of instantaneous and statistical interference constraints on their outage performance. Our results reveal that imposing a statistical interference constraint on the secondary system transmit power is most favored than its spectrum-consuming counter part. Third, we capitalize on our second contribution to investigate cost-effective transmission schemes for cognitive MIMO decode-and-forward (DF) relaying systems employing transmit-antenna selection (TAS) along with maximum-ratio combining (MRC) at the transmitter and receiver sides, respectively. Driven by maximizing either the received signal-to-noise ratio (SNR) or signal-to-interference-plus-noise ratio (SINR), our newly derived outage performance results pertaining to both proposed TAS strategies are shown to entail an involved derivation roadmap yet demonstrate the optimality of the SINR-driven TAS against the detrimental effect of mutual interference incognitive MIMO DF relay systems.