This thesis report presents background knowledge about cognitive radio network (CRN) and investigates performance of underlay cognitive radio networks based on an adaptive power allocation policy of secondary transmitter (SU-Tx). In particular, it has been assumed that SU-Tx and primary user transmitter (PU-Tx) are equipped with a single antenna, while the corresponding receivers are equipped with multiple antennas. Additionally, SU-Tx operates under the joint constraint of its peak transmission power and outage constraint of the primary network. The probability density function (PDF) and cumulative density function (CDF) of the signal to interference and noise ratio (SINR) of SU over Rayleigh fading channel are derived. Using these two functions, a closed-form expression for the outage probability and an approximate expression for ergodic capacity of the considered system are obtained. Matlab simulation results are provided to validate the correctness of the analyses. The results show that simulation and analytical results closely match. The results show that the performance of SU increases as power of PU increases, but behaves the opposite after SU-Tx reaches its peak transmission power. Furthermore, the results reveal that as the number of antennas at the receivers (both SU and PU receivers) increases, the performance of the SU network increases. / maarig2000@gmail.com, marshed18@hotmail.com

In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization and efficiency. However, the penetration of FD communications to the cellular networks domain is challenging due to the imposed uplink/downlink interference. This thesis presents a tractable framework, based on stochastic geometry, to study FD communications in multi-tier cellular networks. Particularly, we assess the FD communications effect on the network performance and quantify the associated gains. The study proves the vulnerability of the uplink to the downlink interference and shows that the improved FD rate gains harvested in the downlink (up to 97%) comes at the expense of a significant degradation in the uplink rate (up to 94%). Therefore, we propose a novel fine-grained duplexing scheme, denoted as α-duplex scheme, which allows a partial overlap between the uplink and the downlink frequency bands. We derive the required conditions to harvest rate gains from the α-duplex scheme and show its superiority to both the FD and half-duplex (HD) schemes. In particular, we show that the α-duplex scheme provides a simultaneous improvement of 28% for the downlink rate and 56% for the uplink rate. We also show that the amount of the overlap can be optimized based on the network design objective. Moreover, backward compatibility is an essential ingredient for the success of new technologies. In the context of in-band FD communication, FD base stations (BSs) should support HD users' equipment (UEs) without sacrificing the foreseen FD gains. The results show that FD-UEs are not necessarily required to harvest rate gains from FD-BSs. In particular, the results show that adding FD-UEs to FD-BSs offers a maximum of 5% rate gain over FD-BSs and HD-UEs case, which is a marginal gain compared to the burden required to implement FD transceivers at the UEs' side. To this end, we shed light on practical scenarios where HD-UEs operation with FD-BSs outperforms the operation when both the BSs and UEs are FD and we find a closed form expression for the critical value of the self-interference cancellation power required for the FD UEs to outperform HD UEs.

In the last decade, wireless applications have witnessed a tremendous growth. This can be envisioned in the surge of smart devices which became almost in everyone's possession, demand for high speed connection and the internet of things (IoT) along with its enabling technologies. Hence, the multiuser interference became the main limiting factor in wireless communications. Moreover, just like diamonds and emeralds, the electromagnetic spectrum is limited and precious. Therefore, the high data rate application may not be satisfied by our current technologies. In order to solve this spectrum scarcity problem, researchers have steered their focus to develop new techniques such as cognitive radio (CR) and in-band full-duplex (FD). However, these systems suffer from the interference problem that can dramatically impede their quality-of-service (QoS). Therefore, investigating communication techniques/systems that can relieve the interference adverse signature becomes imperative. Improper Gaussian signaling (IGS) has been recently shown to outperform the traditional proper Gaussian signaling (PGS) in several interference-limited systems. In this thesis, we use IGS in order to mitigate the interference issue in three different communication settings. IGS has the ability to control the interference signal dimension, and hence, it can be considered as one form of interference alignment. In the first part, we investigate an underlay CR system with in-band FD primary users (PUs) and one-way communication for the secondary user (SU). IGS is employed to alleviate the interference introduced by the SU on the PUs. First, we derive a closed form expression and an upper bound for the SU and PUs outage probabilities, respectively. Second, we optimize the SU signal parameters, represented in its power and the circularity coefficient, to achieve the design objectives of the SU while satisfying certain QoS constraints for the PU under instantaneous, average and partial channel state information (CSI). Finally, we provide some numerical results that demonstrate the advantages that can be reaped by using IGS to access the spectrum of the FD PUs. Specifically, with the existence of week PU direct channels and/or strong SU interference channels, PGS tends to use less transmit power while IGS uses more power along with increasing the signal impropriety. Part 2 studies the potential employment of IGS in FD cooperative settings with non-negligible residual self-interference (RSI). In this part, IGS is used in an attempt to alleviate the RSI adverse effect in full-duplex relaying (FDR). To this end, we derive a tight upper bound expression for the end-to-end outage probability in terms of the relay signal parameters. We further show that the derived upper bound is either monotonic or unimodal in the relay's circularity coefficient. This result allows for easily locating the global optimal point using known numerical methods. Based on the analysis, IGS allows FDR systems to operate even with high RSI. It is shown that, while the communication totally fails with PGS as the RSI increases, the IGS outage probability approaches a fixed value that depends on the channel statistics and target rate. The obtained results show that IGS can leverage higher relay power budgets than PGS to improve the performance, meanwhile it relieves its RSI impact via tuning the signal impropriety. In part 3, we investigate the potential benefits of adopting IGS in a two-hop alternate relaying (AR) system. Given the known benefits of using IGS in interference-limited networks, we propose to use IGS to relieve the inter-relay interference (IRI) impact on the AR system assuming no CSI is available at the source. In this regard, we assume that the two relays use IGS and the source uses PGS. Then, we optimize the degree of impropriety of the relays signal, measured by the circularity coefficient, to maximize the total achievable rate. Simulation results show that using IGS yields a significant performance improvement over PGS, especially when the first hop is a bottleneck due to weak source-relay channel gains and/or strong IRI.

No description available.

Every week there are over a billion new posts to Twitter services and many of those messages contain feedback to companies about their services. One company that recognizes this unused source of information is Netflix. That is why Netflix initiated the development of a system that lets them respond to the millions of Twitter and Netflix users that are acting as sensors and reporting all types of user visible outages. This system enhances the feedback loop between Netflix and its customers by increasing the amount of customer feedback that Netflix receives and reducing the time it takes for Netflix to receive the reports and respond to them. The goal of the SPOONS (Swift Perceptions of Online Negative Situations) system is to use Twitter posts to determine when Netflix users are reporting a problem with any of the Netflix services. This work covers the architecture of the SPOONS system and framework as well as outage detection using tweet classification.

This dissertation is a systematic study of electric power distribution system reliability evaluation and improvement. Reliability evaluation of electric power systems has traditionally been an integral part of planning and operation. Changes in the electric utility coupled with aging electric apparatus create a need for more realistic techniques for power system reliability modeling. This work presents a reliability evaluation technique that combines set theory and Graph Trace Analysis (GTA). Unlike the traditional Markov approach, this technique provides a fast solution for large system reliability evaluation by managing computer memory efficiently with iterators, assuming a single failure at a time. A reconfiguration for restoration algorithm is also created to enhance the accuracy of the reliability evaluation, considering multiple concurrent failures. As opposed to most restoration simulation methods used in reliability analysis, which convert restoration problems into mathematical models and only can solve radial systems, this new algorithm seeks the reconfiguration solution from topology characteristics of the network itself. As a result the new reconfiguration algorithm can handle systems with loops. In analyzing system reliability, this research takes into account time-varying load patterns, and seeks approaches that are financially justified. An exhaustive search scheme is used to calculate optimal locations for Distributed Generators (DG) from the reliability point of view. A Discrete Ascent Optimal Programming (DAOP) load shifting approach is proposed to provide low cost, reliability improvement solutions. As weather conditions have an important effect on distribution component failure rates, the influence of different types of storms has been incorporated into this study. Storm outage models are created based on ten years' worth of weather and power outage data. An observer is designed to predict the number of outages for an approaching or on going storm. A circuit corridor model is applied to investigate the relationship between power outages and lightning activity. / Ph. D.

No description available.

Master of Science / Department of Electrical and Computer Engineering / Anil Pahwa / Unpredictable power outages due to environmental factors such as lighting, wind, trees, and animals, have always been a concern for utilities because they are often unavoidable. This research aims to study squirrel-related outages by modeling past real-life outage data and provide the optimal result which would assist utilities in increasing electric system reliability. This research is a novel approach to benchmark system performance in order to identify areas and durations with higher than expected outages. The model is illustrated with seven years (2005-2011) of animal-related outage data and 14 years of weather data (1998-2011) for four cities in Kansas, used as training data to predict future outages. The past data indicates that the number of outages on any day varies with the seasons and weather conditions on that day. The prediction is based on a Bayesian Model using conditional probability table, which is calculated based on training data. Since future weather conditions are unknown and random, Monte Carlo Simulation is used with the past 14 years of weather data to create different yearly scenarios. These scenarios are then used with the models to predict expected outages. Multiple runs of Monte Carlo analysis provide a probability distribution of expected outages. Further work discusses about cost-to-benefit analysis of implementation of outage mitigation methods. The analysis is performed by considering different combinations of outage reduction and mitigation levels. In this research, eight cases of outage reduction and nine cases of mitigation levels are defined. The probability of benefit is calculated by a statistical approach for every combination. Several optimal strategies are constructed using the probability values and outage history. The outcomes are compared with each other to propose the most beneficial outage mitigation strategy. This research will immensely assist utilities in reducing the outages due to squirrels more effectively with higher benefits and therefore improve reliability of the electricity supply to consumers.

[pt] As variações que ocorrem na estrutura da troposfera ao longo do tempo em relação à sua condição mediana provocam diversos fenômenos que fazem variar aleatoriamente o nível de sinal recebido num enlace rádio. Estas variações aleatórias são denominadas desvanecimentos. Os desvanecimentos são normalmente classificados em rápidos e lentos. Os desvanecimentos rápidos estão geralmente associados ao efeito de multipercurso atmosférico que é fortemente dependente da freqüência, sendo por isto denominados desvanecimentos seletivos, e são a principal causa de degradação do desempenho de enlaces rádio digitais de alta capacidade. Os modelos existentes para a caracterização estatística do desvanecimento por multipercurso são semi-empíricos e baseados em dados experimentais obtidos em regiões de clima temperado, acarretando uma má estimativa quando aplicados a regiões de clima tropical e equatorial. Neste trabalho é apresentada uma avaliação dos métodos existentes para previsão do desempenho de enlaces rádio digitais de alta capacidade, a partir da utilização de dados reais de desempenho extraídos de medidas em um tronco rádio de alta capacidade numa região tropical. / [en] The variations which happen in the troposphere layers throughout the time in relation to the median condition of the signal cause various phenomena that change the received signal level at digital radio relay systems randomly. The random changes are named fading. Fading is normally classified as fast or slow. The former is normally associated with the atmospheric multipath propagation and is strongly dependent on frequency; therefore, this is named selective fading and it is normally the cause of performance degradation in high capacity digital radio relays. The existing models for statistics of multipath fading are semi - empirical and based on experimental data extracts from regions the climate of which is temperate; and this gives a rough estimate with respect to the tropical and equatorial zones. This work presents an evaluation of existing methods of performance prediction for high capacity digital radio relay systems using real performance data obtained from measures of a high capacity digital radio link in operation in the tropical region.

In telecommunications, distributed cooperative communications refer to techniques which allow different users in a wireless network to share or combine their information in order to increase diversity gain or power gain. Unlike conventional point-to-point communications maximizing the performance of the individual link, distributed cooperative communications enable multiple users to collaborate with each other to achieve an overall improvement in performance, e.g., improved range and data rates. The first part of this dissertation focuses the problem of jointly decoding binary messages from a single distant transmitter to a cooperative receive cluster. The outage probability of distributed reception with binary hard decision exchanges is compared with the outage probability of ideal receive beamforming with unquantized observation exchanges. Low- dimensional analysis and numerical results show, via two simple but surprisingly good approximations, that the outage probability performance of distributed reception with hard decision exchanges is well-predicted by the SNR of ideal receive beamforming after subtracting a hard decision penalty of slightly less than 2 dB. These results, developed in non-asymptotic regimes, are consistent with prior asymptotic results (for a large number of nodes and low per-node SNR) on hard decisions in binary communication systems. We next consider the problem of estimating and tracking channels in a distributed transmission system with multiple transmitters and multiple receivers. In order to track and predict the effective channel between each transmit node and each receive node to facilitate coherent transmission, a linear time-invariant state- space model is developed and is shown to be observable but nonstabilizable. To quantify the steady-state performance of a Kalman filter channel tracker, two methods are developed to efficiently compute the steady-state prediction covariance. An asymptotic analysis is also presented for the homogenous oscillator case for systems with a large number of transmit and receive nodes with closed-form results for all of the elements in the asymptotic prediction covariance as a function of the carrier frequency, oscillator parameters, and channel measurement period. Numeric results confirm the analysis and demonstrate the effect of the oscillator parameters on the ability of the distributed transmission system to achieve coherent transmission. In recent years, the development of efficient radio frequency (RF) radiation wireless power transfer (WPT) systems has become an active research area, motivated by the widespread use of low-power devices that can be charged wirelessly. In this dissertation, we next consider a time division multiple access scenario where a wireless access point transmits to a group of users which harvest the energy and then use this energy to transmit back to the access point. Past approaches have found the optimal time allocation to maximize sum throughput under the assumption that the users must use all of their harvested power in each block of the "harvest-then-transmit" protocol. This dissertation considers optimal time and energy allocation to maximize the sum throughput for the case when the nodes can save energy for later blocks. To maximize the sum throughput over a finite horizon, the initial optimization problem is separated into two sub-problems and finally can be formulated into a standard box- constrained optimization problem, which can be solved efficiently. A tight upper bound is derived by relaxing the energy harvesting causality. A disadvantage of RF-radiation based WPT is that path loss effects can significantly reduce the amount of power received by energy harvesting devices. To overcome this problem, recent investigations have considered the use of distributed transmit beamforming (DTB) in wireless communication systems where two or more individual transmit nodes pool their antenna resources to emulate a virtual antenna array. In order to take the advantages of the DTB in the WPT, in this dissertation, we study the optimization of the feedback rate to maximize the energy efficiency in the WPT system. Since periodic feedback improves the beamforming gain but requires the receivers to expend energy, there is a fundamental tradeoff between the feedback period and the efficiency of the WPT system. We develop a new model to combine WPT and DTB and explicitly account for independent oscillator dynamics and the cost of feedback energy from the receive nodes. We then formulate a "Normalized Weighted Mean Energy Harvesting Rate" (NWMEHR) maximization problem to select the feedback period to maximize the weighted averaged amount of net energy harvested by the receive nodes per unit of time as a function of the oscillator parameters. We develop an explicit method to numerically calculate the globally optimal feedback period.