In aeronautical telemetry, the multipath interference usually causes significant performance degradation. As the bit rate of telemetry systems increases, the impairments of multipath interference are more serious. The constant modulus algorithm (CMA) blind equalizer is effective to mitigate the impairments of multipath interference. The CMA adapts the equalizer coefficients to minimize the deviation of the signal envelope from a constant level. This paper presents the performances of the CMA blind equalizer applied for PCM-FM, PCM-BPSK, SOQPSK-TG and ARTM CPM in aeronautical telemetry.

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The advent of spectrum sharing has increased the need for robust interference rejection methods. The Citizens Broadband Radio Service (CBRS) band is soon to be occupied by LTE waveforms and License Assisted Access (LAA) will have LTE signals coexisting with other signals in the 5 GHz band. In anticipation of this need, we present a method for interference rejection of cyclostationary signals, which can also help avoid interference through better detection of low power co-channel signals. The method proposed in this thesis consists of a frequency-shift (FRESH) filter which acts as a whitening filter, canceling the interference by exploiting its cyclostationarity. It learns the cyclostationary characteristics of the interferer blindly, through a property restoration algorithm which aims to drive the spectrum to white noise. The property restoration algorithm, inspired by the constant modulus algorithm (CMA), is applied to each frequency bin to determine the optimal coefficients for the proposed CMA FRESH whitening filter (CFW). The performance of the CFW in interference rejection is compared to a time-invariant version, and proposed use cases are analyzed. The use cases consist of the rejection of a high powered, wider bandwidth interferer which is masking the signal-of-interest (SOI). The interferer is rejected blindly, with no knowledge of its characteristics. We analyzed signal detection performance in the case that the SOI is another user with much lower power, for multiple types of SOIs ranging from BPSK to OFDM. We also deal with the case that the SOI is to be received and demodulated; we recover it and compare resulting bit error rates to state of the art FRESH filters. The results show significantly better signal detection and recovery. / Master of Science / Wireless communication is complicated by the fact that multiple radios may be attempting to transmit at the same frequency, time and location concurrently. This scenario may be a due to malicious intent by certain radios (jamming), or mere confusion due to a lack of knowledge that another radio is transmitting in the same channel. The latter scenario is more common due to congested wireless spectrum, as the number of devices increases exponentially. In either case, interference results. We present a novel interference rejection method in this work, one that is blind to the properties of the interferer and adapts to cancel it. It follows the philosophy of property restoration as extolled by the constant modulus algorithm (CMA) and is a frequency shift (FRESH) filter, hence the name. The process of restoring the wireless spectrum to white noise is what makes it a whitening filter, and is also how it adapts to cancel interference. Such a filter has myriad possible uses, and we examine the use case of rejecting interference to detect or recover the signal-of-interest (SOI) that we are attempting to receive. We present performance results in both cases and compare with conventional time-invariant filters and state of the art FRESH filters.

In this thesis, we investigate the use of adaptive antenna algorithms for OFDM systems to suppress interference in various channel conditions including narrowband and wideband interference, flat and frequency selective fading. We propose a novel frequency-domain beamformer, based on the linearly constrained modified constant modulus hybrid LMS (LCMCM-HLMS) algorithm for OFDM systems to improve the performance of interference suppression in AWGN channel with narrowband interference, Rayleigh fast fading channel with phase distortion, and the multipath environment. To verify the merits of the frequency-domain beamformer, the effect due to narrowband interference and random phase distortion are investigated. Moreover, to improve the performance of adaptive beamforming algorithm, the frequency-domain linearly constrained modified constant modulus hybrid LMS (LCMCM-HLMS) algorithm is proposed. Computer simulation results show that the proposed frequency-domain LCMCM-HLMS beamformer has good capability of interference supression in various environment, and can mitigate the phase distortion of channel. However, in the time-domain beamformer based on LMS [33], RLS ,LC-LMS and LC-FLS algorithm for OFDM systems, the performance may severely degraded under some situations. We will show that in terms of output SINR, beampatern, received signal constellation and mean square error (MSE), for narrowband interference suppression in AWGN channel, phase distortion in Rayleigh fast fading channel and the multipath environment.

We consider the problem of equalizing data blocks of signals, which have been transmitted over an aeronautical channel using two different modulation schemes. The equalization is performed using the block-processing constant modulus algorithm (CMA), and in order to achieve real-time processing a Fast Fourier Transform (FFT) is used to compute the gradient of this cost function during equalization. The equalizer length is chosen to be five times of the channel length. For the first experiment, we present the result of equalizing a set of measured data, which was modulated and transmitted using the iNET packet structure with SOQPSK modulation. In this case, the CMA equalizer is first initialized using MMSE and the equalizer coefficients are then updated once, using each entire block (iNET packet). In the second experiment, we apply the FFT-based block processing equalizer to received data blocks of QPSK signals, which have been randomly generated and transmitted over an aeronautical channel. A modified constant modulus algorithm and alphabet matched algorithm (CMA + AMA) equalizer is used to recover these data blocks. For this case of QPSK signals, the equalizer performance is evaluated over 500 Monte Carlo runs, using the average symbol error rate (SER).

Orientadora: Profa. Dra. Aline de Oliveira Neves Panazio / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia da Informação, 2014. / Redes de sensores sem o (WSN - Wireless Sensor Networks) têm sido usadas na observação de fenômenos, identicação de sistemas, equalização de canais, além de aplicações nas mais diversas áreas. Considerando o caso de redes homogêneas com protocolo ponto a ponto, nas quais os sensores são capazes de processar suas informações e se comunicar com sensores vizinhos, diversos algoritmos adaptativos vêm sendo aplicados no processamento dos dados medidos. Estes algoritmos podem ser supervisionados ou não supervisionados. Buscando estimar parâmetros comuns através de um processamento distribuído, a topologia da rede passa a ser uma característica importante e precisa ser levada em conta nos algoritmos utilizados. Tais algoritmos operam em modo de difusão, considerando a troca de informações entre sensores vizinhos na atualização dos coecientes dos ltros adaptativos de cada sensor. O mapeamento da topologia da rede é feito de forma matricial através das chamadas matrizes de combinação. Neste trabalho, estudamos o impacto da escolha da matriz de combinação no desempenho dos algoritmos supervisionados. No caso de algoritmos não supervisionados, como a única proposta encontrada na literatura considerava um caso bastante restrito em que o algoritmo só poderia ser aplicado a uma rede com topologia em anel e comunicação unidirecional entre os nós, propomos um novo algoritmo capaz de operar em modo de difusão em qualquer topologia, baseado no clássico critério do módulo constante. O algoritmo proposto é simulado em diversas situações, sempre apresentando vantagens em relação a uma rede sem cooperação entre os nós. / Wireless sensor networks (WSN) have been used in the observation of several phenomena, system identication, channel equalization, and others. Considering the case of homogeneous networks with point to point protocol, in which the sensors are able to process their information and communicate with neighbors, various adaptive algorithms have been applied in the processing of measured data. These algorithms can be supervised or unsupervised. Seeking to estimate common parameters across a distributed processing, network topology becomes an important feature and must be taken into account in the algorithms used. Such algorithms operate in diusion mode, that is, considering the exchange of information between sensors to update the coecients of the adaptive lters. Thenetwork topology is mapped through the use of a matrix, denoted combination matrix. In this work, we study the impact of the choice of the combination matrix on the performance of supervised algorithms. In the case of blind methods, the only technique found in the literature was applied to the specic case of a network with ring topology and unidirectional communication between nodes. Thus, we propose a new algorithm capable of operating in diusion mode on any topology, based on the classical constant modulus criterion. The proposed algorithm is simulated in several scenarios, always presenting advantages over a network without cooperation between nodes.

O objetivo da desconvolução cega de imagens é restaurar uma imagem degradada sem usar informação da imagem real ou da função de degradação. O mapeamento dos níveis de cinza de uma imagem em um sinal de comunicação possibilita o uso de técnicas de equalização cega de canais para a restauração de imagens. Neste trabalho, propõe-se o uso de um esquema para desconvolução cega de imagens baseado na combinação convexa de um equalizador cego com um equalizador no modo de decisão direta. A combinação também é adaptada de forma cega, o que possibilita o chaveamento automático entre os filtros componentes. Dessa forma, o esquema proposto é capaz de atingir o desempenho de um algoritmo de filtragem adaptativa supervisionada sem o conhecimento prévio da imagem original. O desempenho da combinação é ilustrado por meio de simulações, que comprovam a eficiência desse esquema quando comparado a outras soluções da literatura. / The goal of blind image deconvolution is to restore a degraded image without using information from the actual image or from the point spread function. The mapping of the gray levels of an image into a communication signal enables the use of blind equalization techniques for image restoration. In this work, we use a blind image deconvolution scheme based on the convex combination of a blind equalizer with an equalizer in the decision-directed mode. The combination is also blindly adapted, which enables automatic switching between the component filters. Thus, the proposed scheme is able to achieve the performance of a supervised adaptive filtering algorithm without prior knowledge of the original image. The performance of the combination is illustrated by simulations, which show the efficiency of this scheme when compared to other solutions in the literature.

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / Este trabalho trata da proposiÃÃo de algoritmos para equalizaÃÃo cega de canais lineares e nÃao-lineares inspirados no Algoritmo do MÃdulo Constante (CMA). O CMA funciona de maneira bastante eficiente com constelaÃÃes nas quais todos os pontos possuem a mesma amplitude, como em modulaÃÃes do tipo Phase Shift Keying (PSK). Entretanto, quando os pontos da constelaÃÃo podem assumir diferentes valores de amplitudes, como em modulaÃÃes do tipo Quadrature Amplitude Modulation (QAM), o CMA e seus derivados muitas vezes nÃo funcionam de forma satisfatÃria. Desta forma, as tÃcnicas aqui propostas sÃo projetadas para melhorar a performance do CMA em termos de velocidade de convergÃncia e precisÃo, quando operando em sinais transmitidos com diversos mÃdulos, em particular para a modulaÃÃo QAM. Assim como o CMA, para possuir um bom apelo prÃtico, essas tÃcnicas devem apresentar bom compromisso entre complexidade, robustez e desempenho. Para tanto, as tÃcnicas propostas utilizam o Ãltimo sÃmbolo decidido para definir uma estimaÃÃo de raio de referÃncia para a saÃda do equalizador. De fato, esses algoritmos podem ser vistos como generalizaÃÃes do CMA e de alguns derivados do CMA para constelaÃÃes com mÃltiplos raios. A proposiÃÃo de algoritmos do tipo gradiente estocÃstico à concluÃda com o desenvolvimento de tÃcnicas originais, baseadas no CMA, para equalizaÃÃo de canais do tipo Wiener, que consiste em um filtro linear com memÃria, seguido por um filtro nÃo-linear sem memÃria. As expressÃes para a adaptaÃÃo do equalizador sÃo encontradas com o auxÃlio de uma notaÃÃo unificada para trÃs diferentes estruturas: i) um filtro de Hammerstein; ii) um filtro de Volterra diagonal; e iii) um filtro de Volterra completo. Um estudo teÃrico acerca do comportamento do principal algoritmo proposto, o Decision Directed Modulus Algorithm (DDMA) à realizado. SÃo analisadas a convergÃncia e a estabilidade do algoritmo atravÃs de uma anÃlise dos pontos de mÃnimo de sua funÃÃo custo. Outro objetivo à encontrar o valor teÃrico do Erro MÃdio QuadrÃtico MÃdio em Excesso - Excess Mean Square Error (EMSE) fornecido pelo DDMA considerando-se o caso sem ruÃdo. Ao final, à feito um estudo em que se constata que o algoritmo DDMA possui fortes ligaÃÃes com a soluÃÃo de Wiener e com o CMA. VersÃes normalizadas, bem como versÃes do tipo Recursive Least Squares (RLS), dos algoritmos do tipo gradiente estocÃstico estudados sÃo tambÃm desenvolvidas. Cada famÃlia de algoritmos estudada fie composta por quatro algoritmos com algumas propriedades interessantes e vantagens sobre as tÃcnicas clÃssicas, especialmente quando operando em sinais QAM de ordem elevada. TambÃm sÃo desenvolvidas versÃes normalizadas e do tipo RLS dos algoritmos do tipo CMA estudados para equalizaÃÃo de canais nÃo-lineares. O comportamento de todas as famÃlias de algoritmos desenvolvidos à testado atravÃs de simulaÃÃes computacionais, em que à verificado que as tÃcnicas propostas fornecem ganhos significativos em desempenho, em termos de velocidade de convergÃncia e erro residual, em relaÃÃo Ãs tÃcnicas clÃssicas. / This work studies and proposes algorithms to perform blind equalization of linear and nonlinear channels inspired on the Constant Modulus Algorithm (CMA). The CMA works very well for modulations in which all points of the signal constellation have the same radius, like in Phase Shift Keying (PSK) modulations. However, when the constellation points are characterized by multiple radii, like in Quadrature Amplitude Modulation (QAM) signals, the CMA does not work properly in many situations. Thus, the techniques proposed here are designed to improve the performance of the CMA, in terms of speed of convergence and residual error, when working with signals transmitted with multiple magnitude, in particular with QAM signals. As well as for the CMA, these techniques should have a good compromise among performance, complexity and robustness. To do so, the techniques use the last decided symbol to estimate reference radius to the output of the equalizer. In fact, they can be seen as modifications of the CMA and of some of its derivatives for constellations with multiple radii. The proposition of stochastic gradient algorithms is concluded with the development of new adaptive blind techniques to equalize channels with a Wiener structure. A Wiener filter consists of a linear block with memory followed by a memoryless nonlinearity, by using the CMA. We develop expressions for the adaptation of the equalizer using a unified notation for three different equalizer filter structures: i) a Hammerstein filter, ii) a diagonal Volterra filter and iii) a Volterra filter. A theoretical analysis of the main proposed technique, the Decision Directed Modulus Algorithm (DDMA), is also done. We study the convergence and the stability of the DDMA by means of an analysis of the minima of the DDM cost function. We also develop an analytic expression for the Excess Mean Square Error (EMSE) provided by the DDMA in the noiseless case. Then, we nd some interesting relationships among the DDM, the CM and the Wiener cost functions. We also develop a class of normalized algorithms and a class of Recursive Least Squares (RLS)-type algorithms for blind equalization inspired on the CMA-based techniques studied. Each family is composed of four algorithms with desirable properties and advantages over the original CM algorithms, specially when working with high-level QAM signals. Normalized and RLS techniques for equalization of Wiener channels are also developed. The behavior of the proposed classes of algorithms discussed is tested by computational simulations. We verify that the proposed techniques provide significative gains in performance, in terms of speed of convergence and residual error, when compared to the classical algorithms.

Neste trabalho, são propostos e analisados algoritmos autodidatas eficientes para a equalização de canais de comunicação, considerando a transmissão de sinais QAM (quadrature amplitude modulation). Suas funções de erro são construídas de forma a fazer com que o erro de estimação seja igual a zero nas coordenadas dos símbolos da constelação. Essa característica os possibilita ter um desempenho similar ao de um algoritmo de equalização supervisionada como o NLMS (normalized least mean-square), independentemente da ordem da constelação QAM. Verifica-se analiticamente que, sob certas condições favoráveis para a equalização, os vetores de coeficientes dos algoritmos propostos e a correspondente solução de Wiener são colineares. Além disso, usando a informação da estimativa do símbolo transmitido e de seus símbolos vizinhos, esquemas de baixo custo computacional são propostos para aumentar a velocidade de convergência dos algoritmos. No caso do algoritmo baseado no critério do módulo constante, evita-se sua divergência através de um mecanismo que descarta estimativas inconsistentes dos símbolos transmitidos. Adicionalmente, apresenta-se uma análise de rastreio (tracking), que permite obter expressões analíticas para o erro quadrático médio em excesso dos algoritmos propostos em ambientes estacionários e não-estacionários. Através dessas expressões, verifica-se que com sobreamostragem, ausência de ruído e ambiente estacionário, os algoritmos propostos podem alcançar a equalização perfeita, independentemente da ordem da constelação QAM. Os algoritmos são estendidos para a adaptação conjunta dos filtros direto e de realimentação do equalizador de decisão realimentada, levando-se em conta um mecanismo que evita soluções degeneradas. Resultados de simulação sugerem que a utilização dos esquemas aqui propostos pode ser vantajosa na recuperação de sinais QAM, fazendo com que seja desnecessário o chaveamento para o algoritmo de decisão direta. / In this work, we propose efficient blind algorithms for equalization of communication channels, considering the transmission of QAM (quadrature amplitude modulation) signals. Their error functions are constructed in order to make the estimation error equal to zero at the coordinates of the constellation symbols. This characteristic enables the proposed algorithms to have a similar performance to that of a supervised equalization algorithm as the NLMS (normalized least mean-square), independently of the QAM order. Under some favorable conditions, we verify analytically that the coefficient vector of the proposed algorithms are collinear with the Wiener solution. Furthermore, using the information of the symbol estimate in conjunction with its neighborhood, we propose schemes of low computational cost in order to improve their convergence rate. The divergence of the constant-modulus based algorithm is avoided by using a mechanism, which disregards nonconsistent estimates of the transmitted symbols. Additionally, we present a tracking analysis in which we obtain analytical expressions for the excess mean-square error in stationary and nonstationary environments. From these expressions, we verify that using a fractionally-spaced equalizer in a noiseless stationary environment, the proposed algorithms can achieve perfect equalization, independently of the QAM order. The algorithms are extended to jointly adapt the feedforward and feedback filters of the decision feedback equalizer, taking into account a mechanism to avoid degenerative solutions. Simulation results suggest that the proposed schemes may be advantageously used to recover QAM signals and make the switching to the decision direct mode unnecessary.

O objetivo da desconvolução cega de imagens é restaurar uma imagem degradada sem usar informação da imagem real ou da função de degradação. O mapeamento dos níveis de cinza de uma imagem em um sinal de comunicação possibilita o uso de técnicas de equalização cega de canais para a restauração de imagens. Neste trabalho, propõe-se o uso de um esquema para desconvolução cega de imagens baseado na combinação convexa de um equalizador cego com um equalizador no modo de decisão direta. A combinação também é adaptada de forma cega, o que possibilita o chaveamento automático entre os filtros componentes. Dessa forma, o esquema proposto é capaz de atingir o desempenho de um algoritmo de filtragem adaptativa supervisionada sem o conhecimento prévio da imagem original. O desempenho da combinação é ilustrado por meio de simulações, que comprovam a eficiência desse esquema quando comparado a outras soluções da literatura. / The goal of blind image deconvolution is to restore a degraded image without using information from the actual image or from the point spread function. The mapping of the gray levels of an image into a communication signal enables the use of blind equalization techniques for image restoration. In this work, we use a blind image deconvolution scheme based on the convex combination of a blind equalizer with an equalizer in the decision-directed mode. The combination is also blindly adapted, which enables automatic switching between the component filters. Thus, the proposed scheme is able to achieve the performance of a supervised adaptive filtering algorithm without prior knowledge of the original image. The performance of the combination is illustrated by simulations, which show the efficiency of this scheme when compared to other solutions in the literature.