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Robust nonparametric spectral estimation includes generating an accurate estimate of the Power Spectral Density (PSD) for a given set of data while trying to minimize the bias due to data outliers. Robust nonparametric spectral estimation is applied in the domain of electrical communications and digital signal processing when a PSD estimate of the electromagnetic spectrum is desired (often for the goal of signal detection), and when the spectrum is also contaminated by Impulsive Noise (IN). Power Line Communication (PLC) is an example of a communication environment where IN is a concern because power lines were not designed with the intent to transmit communication signals. There are many different noise models used to statistically model different types of IN, but one popular model that has been used for PLC and various other applications is called the Middleton Class A model, and this model is extensively used in this thesis. The performances of two different nonparametric spectral estimation methods are analyzed in IN: the Welch method and the multitaper method. These estimators work well under the common assumption that the receiver noise is characterized by Additive White Gaussian Noise (AWGN). However, the performance degrades for both of these estimators when they are used for signal detection in IN environments. In this thesis basic robust estimation theory is used to modify the Welch and multitaper methods in order to increase their robustness, and it is shown that the signal detection capabilities in IN is improved when using the modified robust estimators. / Master of Science / One application of blind spectral estimation is blind signal detection. Unlike a car radio, where the radio is specifically designed to receive AM and PM radio waves, sometimes it is useful for a radio to be able to detect the presence of transmitted signals whose characteristics are not known ahead of time. Cognitive radio is one application where this capability is useful. Often signal detection is inhibited by Additive White Gaussian Noise (AWGN). This is analogous to trying to hear a friend speak (signal detection) in a room full of people talking (background AWGN). However, some noise environments are more impulsive in nature. Using the previous analogy, the background noise could be loud banging caused by machinery; the noise will not be as constant as the chatter of the crowd, but it will be much louder. When power lines are used as a medium for electromagnetic communication (instead of just sending power), it is called Power Line Communication (PLC), and PLC is a good example of a system where the noise environment is impulsive. In this thesis, methods used for blind spectral estimation are modified to work reliably (or robustly) for impulsive noise environments.

In many modern wireless and wireline communication networks, the interference power from other communication and non-communication devices is increasingly dominating the background noise power, leading to interference limited communication systems. Conventional communication systems have been designed under the assumption that noise in the system can be modeled as additive white Gaussian noise (AWGN). While appropriate for thermal noise, the AWGN model does not always capture the interference statistics in modern communication systems. Interference from uncoordinated users and sources is particularly harmful to communication performance because it cannot be mitigated by current interference management techniques. Based on previous statistical-physical models for uncoordinated wireless interference, this dissertation derives similar models for uncoordinated interference in PLC networks. The dissertation then extends these models for wireless and powerline interference to include temporal dependence among amplitude samples. The extensions are validated with measured data. The rest of this dissertation utilizes the proposed models to design receivers in interference limited environments. Prior designs generally adopt suboptimal approaches and often ignore the problem of channel estimation which limits their applicability in practical systems. This dissertation uses the graphical model representation of the OFDM system to propose low-complexity message passing OFDM receivers that leverage recent results in soft-input soft-output decoding, approximate message passing, and sparse signal recovery for joint channel/interference estimation and data decoding. The resulting receivers provide huge improvements in communication performance (more than 10dB) over the conventional receivers at a comparable computational complexity. Finally, this dissertation addresses the design of robust receivers that can be deployed in rapidly varying environments where the interference statistics are constantly changing. / text

Orientador: Maurílio Boaventura / Banca: Adilson Gonzaga / Banca: Eliana Xavier Linhares de Andrade / Resumo: Neste trabalho propõe-se um filtro mediano seletivo e um filtro híbrido para eliminação de ruído impulsivo em imagens digitais monocromáticas. O primeiro é baseado em uma modificação do filtro mediano por meio de um detector de ruído impulsivo. O segundo é obtido combinando-se o filtro mediano seletivo com um modelo de retoque digital. A remoção de ruído impulsivo em uma imagem colorida é realizada por meio da extensão dos filtros propostos para cada canal de cor da imagem. Os experimentos realizados indicam que os métodos propostos são eficazes na restauração de imagens com grandes densidades de ruído. / Abstract: In this paper a selective median filter and a hybrid filter for removing impulsive noise in digital grayscale images are proposed. The first is a median filter modification based on impulsive noise detector. The second is obtained by combining the selective median filter with a digital inpainting model. The noise removal in color image is obtained by extending the proposed filters for each color channel of the image. The experiments indicated that the proposed methods are powerful in restoring images with high densities noise. / Mestre

Turbo Trellis-Coded Modulation (TTCM) is an attractive scheme for higher data rate transmission, since it combines the impressive near Shannon limit error correcting ability of turbo codes with the high spectral efficiency property of TCM codes. We build a punctured parity-concatenated trellis codes in which a TCM code is used as the inner code and a simple parity-check code is used as the outer code. It can be constructed by simple repetition, interleavers, and TCM and functions as standard TTCM but with much lower complexity regarding real world implementation. An iterative bit MAP decoding algorithm is associated with the coding scheme. Orthogonal Frequency Division Multiplexing (OFDM) modulation has been a promising solution for efficiently capturing multipath energy in highly dispersive channels and delivering high data rate transmission. One of UWB proposals in IEEE P802.15 WPAN project is to use multi-band OFDM system and punctured convolutional codes for UWB channels supporting data rate up to 480Mb/s. The HomePlug Networking system using the medium of power line wiring also selects OFDM as the modulation scheme due to its inherent adaptability in the presence of frequency selective channels, its resilience to jammer signals, and its robustness to impulsive noise in power line channel. The main idea behind OFDM is to split the transmitted data sequence into N parallel sequences of symbols and transmit on different frequencies. This structure has the particularity to enable a simple equalization scheme and to resist to multipath propagation channel. However, some carriers can be strongly attenuated. It is then necessary to incorporate a powerful channel encoder, combined with frequency and time interleaving. We examine the possibility of improving the proposed OFDM system over UWB channel and HomePlug powerline channel by using our Turbo TCM with QAM constellation for higher data rate transmission. The study shows that the system can offer much higher spectral efficiency, for example, 1.2 Gbps for OFDM/UWB which is 2.5 times higher than the current standard, and 39 Mbps for OFDM/HomePlug1.0 which is 3 times higher than current standard. We show several essential requirements to achieve high rate such as frequency and time diversifications, multi-level error protection. Results have been confirmed by density evolution. The effect of impulsive noise on TTCM coded OFDM system is also evaluated. A modified iterative bit MAP decoder is provided for channels with impulsive noise with different impulsivity.

Au cours de ces dernières années, le réseau électrique est devenu un candidat incontournable pour la transmission de données à haut débit à l’intérieur des bâtiments. De nombreuses solutions sont actuellement à l’étude afin d’optimiser ces technologies connues sous le nom Courants Porteurs en Ligne (CPL) ou PLC (Power-Line Communications). La technique MIMO (Multiple-Input Multiple-Output) a été tout récemment transposée au réseau filaire électrique pour lequel différents modes d’alimentation peuvent être envisagés entre la phase, le neutre et la terre. Dans le cadre de cette thèse, nous proposons deux contributions originales à l’étude des communications numériques sur le réseau électrique à l’intérieur des bâtiments. La première contribution concerne la modélisation du canal MIMO-PLC. En repartant d’un modèle du canal paramétrique SISO (Single-Input Single-Output) connu dans la littérature, nous proposons un modèle du canal MIMO en considérant un nouveau paramètre caractérisant la corrélation spatiale. Le modèle proposé permet de représenter fidèlement la corrélation spatiale des mesures effectuées à l’échelle européenne. La deuxième contribution concerne le bruit impulsif présent sur le réseau électrique domestique qui constitue un problème majeur dans les systèmes de communications. Nous proposons une méthode basée sur la notion de capacité de coupure afin d’optimiser le débit moyen dans les systèmes OFDM (Orthogonal Frequency Division Multiplexing) soumis aux bruits impulsifs. D’abord, nous étudions la capacité du système en fonction d’une marge de bruit fournie aux symboles transmis. Ensuite, nous déterminons l’expression analytique de la probabilité de coupure (outage) d’un symbole OFDM en fonction de cette marge, en étudiant de manière détaillée l’interaction entre l’impulsion de bruit et le symbole. A partir de ces deux calculs, nous déduisons la capacité de coupure. Puis, nous proposons une approche qui maximise l’espérance mathématique du débit reçu. Finalement, nous présentons les résultats obtenus dans le cas particulier d’une transmission à haut débit sur PLC en présence de bruits impulsifs. / In recent years, the electrical network has become an essential candidate for high-speed data transmission inside buildings. Many solutions are currently underway in order to optimize these technologies known under the name of in-home Power-Line Communications (PLC). Multiple-Input Multiple-Output (MIMO) technique has recently been transposed into power-line networks for which different signal feeding possibilities can be considered between phase, neutral and earth wires. In this thesis, we propose two original contributions to indoor broadband PLC. The first contribution concerns the MIMO-PLC channel modeling. Based on a Single-Input Single-Output (SISO) parametric channel model presented in the literature, we propose a MIMO one by considering a new parameter which characterizes the spatial correlation. The proposed model enables an accurate description of the spatial correlation of European MIMO PLC field measurements. The second contribution is related to the impulsive noise present in power-line networks which constitutes a major problem in communications systems. We propose an outage capacity approach in order to optimize the average data rate in Orthogonal Frequency Division Multiplexing (OFDM) systems affected by impulsive noise. First, we study the channel capacity as a function of a noise margin provided to the transmitted symbols. Then we determine the analytical expression of the outage probability of an OFDM symbol in terms of the noise margin, by studying in detail the interaction between the noise impulse and the symbol. Based on the two aforementioned relations, we deduce the outage capacity. Then we propose an approach that enables to maximize the average system data rate. Finally, we present the results in the particular case of indoor broadband PLC in the presence of impulsive noise.

Smart grid aims at improving the efficiency, reliability, security, and quality of service (QoS) of the current electricity grid by exploiting the advances in communication and information technology. In parallel to size of the electricity grid, smart grid communication infrastructure should cover a very large geographical area that may extend from remote generation sites to densely populated residential regions and inside buildings, homes, and electricity-power-system environments. In such an extensive communication network, different communication technologies operating on different communication medium are likely to coexist. Among the communication technologies available, wireless and power line communication (PLC) based solutions are comparatively attractive especially considering cost of the initial investment required for the realization of a communication network with such an immense size. In this dissertation, a detailed investigation of wireless and PLC channel characteristics of the smart grid networks is presented. Among the topics discussed are the time variation characteristics of wireless channels, root-mean-squared (RMS) delay spread and path amplitude statistics of PLC channels, and the impact of impulsive noise on orthogonal frequency division multiplexing (OFDM) systems.

Made available in DSpace on 2014-06-11T19:26:55Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-02-26Bitstream added on 2014-06-13T19:47:27Z : No. of bitstreams: 1 almeida_mp_me_sjrp.pdf: 4937582 bytes, checksum: 4d9c67bc8dda1a2e1a742ee59be238fa (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Neste trabalho propõe-se um filtro mediano seletivo e um filtro híbrido para eliminação de ruído impulsivo em imagens digitais monocromáticas. O primeiro é baseado em uma modificação do filtro mediano por meio de um detector de ruído impulsivo. O segundo é obtido combinando-se o filtro mediano seletivo com um modelo de retoque digital. A remoção de ruído impulsivo em uma imagem colorida é realizada por meio da extensão dos filtros propostos para cada canal de cor da imagem. Os experimentos realizados indicam que os métodos propostos são eficazes na restauração de imagens com grandes densidades de ruído. / In this paper a selective median filter and a hybrid filter for removing impulsive noise in digital grayscale images are proposed. The first is a median filter modification based on impulsive noise detector. The second is obtained by combining the selective median filter with a digital inpainting model. The noise removal in color image is obtained by extending the proposed filters for each color channel of the image. The experiments indicated that the proposed methods are powerful in restoring images with high densities noise.

In recent years, linear prediction voice encoders have become very efficient in terms of computing execution time and channel bandwidth usage while providing, in the absence of im- pulsive noise, natural sounding synthetic speech signals. This good performance has been achieved via the use of a maximum likelihood parameter estimation of an auto-regressive model of order ten that best fits the speech signal under the assumption that the signal and the noise are Gaussian stochastic processes. However, this method breaks down in the presence of impulse noise, which is common in practice, resulting in harsh or non-intelligible audio signals. In this paper, we propose a robust estimator of correlation, the Phase-Phase correlator that is able to cope with impulsive noise. Utilizing this correlator, we develop a Robust Mixed Excitation Linear Prediction encoder that provides improved audio quality for voiced, unvoiced, and transition speech segments. This is achieved by applying a statistical test to robust Mahalanobis distances for identifying the outliers in the corrupted speech signal, which are then replaced with filtered signals. Simulation results reveal that the proposed method outperforms in variance, bias, and breakdown point three other robust approaches based on the arcsin law, the polarity coincidence correlator, and the median- of-ratio estimator without sacrificing the encoder bandwidth efficiency and the compression gain while remaining compatible with real-time applications. Furthermore, in the presence of impulsive noise, the proposed speech encoder speech perceptual quality also outperforms the state of the art in terms of mean opinion score. / Doctor of Philosophy / Impulsive noise is a natural phenomenon in everyday experience. Impulsive noise can be analogous to discontinuities or a drastic change in natural progressions of events. Specifically in this research the disrupting events can occur in signals such as speech, power transmission, stock market, communication systems, etc. Sudden power outage due to lighting, maintenance or other catastrophic events are some of the reasons why we may experience performance degradation in our electronic devices. Another example of impulsive noise is when we play an old damaged vinyl records, which results in annoying clicking sounds. At the time instance of each click, the true music or speech or simply the audible waveform is completely destroyed. Other examples of impulse noise is a sudden crash in the stock market; a sudden dive in the market can destroy the regression and future predictions. Unfortunately, in the presence of impulsive noise, classical methods methods are unable to filter out the impulse corruptions. The intended filtering objective of this dissertation is specific, but not limited, to speech signal processing. Specifically, research different filter model to determine the optimum method of eliminating impulsive noise in speech. Note, that the optimal filter model is different for time series signal model such as speech, stock market, power systems, etc. In our studies we have shown that our speech filter method outperforms the state of the art algorithms. Another major contribution of our research is in speech compression algorithm that is robust to impulse noise in speech. In digital signal processing, a compression method entails in representing the same signal with less data and yet convey the the same same message as the original signal. For example, human auditory system can produce sounds in the range of approximately 60 Hz and 3500 Hz, another word speech can occupy approximately 4000 Hz in frequency space. So the challenge is, can we compress speech in one of half of that space, or even less. This is a very attractive proposition because frequency space is limited but the wireless service providers desires to service as many users as possible without sacrificing quality and ultimately maximize the bottom line. Encoding impulse corrupted speech produces harsh quality of synthesized audio. We have shown if the encoding is done with the proposed method, synthesized audio quality is far superior to the sate of the art.