Dissertations / Theses on the topic 'Constant Modulus Algorithm'

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).

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 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.

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.

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.

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.

Orientadora: Profa. Dra. Aline de Oliveira Neves Panazio
Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia da Informação, Santo André, 2018.
Este trabalho dedica-se ao estudo de algoritmos de filtragem adaptativa autodidata no modo difusão, com aplicações em redes de sensores sem fio (RSSF). No modo difusão, os nós sensores da rede possuem poder de processamento local e trocam informações com seus vizinhos. Neste trabalho, propomos dois algoritmos utilizando como base o algoritmo CMA no modo Difusão (CMAD), com duas abordagens distintas da técnica Set-Membership. O primeiro baseia-se no algoritmo Set-Membership Least Mean Squares (SM-LMS), desenvolvido também no modo difusão. Estendemos o algoritmo para o contexto não supervisionado, denotando por Algoritmo Set-Membership CMA no modo Difusão (SM-CMAD). Mostramos que este algoritmo apresenta desempenho melhor ou similar ao CMAD, em termos de velocidade de convergência, patamar de interferência intersimbólica (IIS) e possuindo a importante vantagem de reduzir as trocas de informações entre os nós, economizando energia e recursos da rede. O segundo algoritmo proposto se baseia no Set-Membership do Módulo Constante (SM-CM), o qual estendemos para o contexto de redes de sensores sem fio no modo difusão. Tal algoritmo é denotado por Algoritmo Set-membership CMA no modo Difusão Square-root Gamma (SM-CMAD-SG). Novamente o algoritmo apresenta um bom desempenho quando comparado com o CMAD e, quando comparado ao SM-CMAD, vemos que sua principal vantagem está na economia em termos de atualizações dos coeficientes do filtro, que chega a valores acima de 70% em diversos cenários de simulação, sem grandes perdas de desempenho economizando energia.
This work is devoted to the study of unsupervised adaptive filtering algorithms in diffusion mode, with applications in wireless sensor networks (WSNs). In diffusion mode, network sensing nodes have local processing power and exchange information with their neighbors. In this work, we propose two algorithms based on the CMA algorithm in Diffusion mode (CMAD), with two different approaches to the Set-Membership technique. The first one is based on the Set-Membership Least Mean Squares (SM-LMS) algorithm, also developed in the diffusion mode. We extend the algorithm to the unsupervised context, denoting by Set-Membership CMA in Diffusion mode (SM-CMAD). We show that this algorithm presents better or similar performance to CMAD, in terms of convergence speed, intersymbol interference threshold (IIS), and has the important advantage of reducing the exchange of information between nodes, saving energy and network resources. The second proposed algorithm is based on the Set-Membership of the Constant Modulus (SM-CM), which we extend to the context of wireless sensor networks in the diffusion mode. This algorithm is denoted by the Set-membership CMA in Diffusion mode Square-root Gamma (SM-CMAD-SG). This algorithm performs well when compared to CMAD and, when compared to SM-CMAD, we see that its main advantage lies in the economy in terms of the update of the filter coefficients, which reaches values above 70% in several scenarios without loss of performance, saving energy.

This thesis attempts to address the problem of how best to remedy different types of channel distortions on speech when that speech is to be used in automatic speaker recognition and verification systems. Automatic speaker recognition is when a person's voice is analysed by a machine and the person's identity is worked out by the comparison of speech features to a known set of speech features. Automatic speaker verification is when a person claims an identity and the machine determines if that claimed identity is correct or whether that person is an impostor. Channel distortion occurs whenever information is sent electronically through any type of channel whether that channel is a basic wired telephone channel or a wireless channel. The types of distortion that can corrupt the information include time-variant or time-invariant filtering of the information or the addition of 'thermal noise' to the information, both of these types of distortion can cause varying degrees of error in information being received and analysed. The experiments presented in this thesis investigate the effects of channel distortion on the average speaker recognition rates and testing the effectiveness of various channel compensation algorithms designed to mitigate the effects of channel distortion. The speaker recognition system was represented by a basic recognition algorithm consisting of: speech analysis, extraction of feature vectors in the form of the Mel-Cepstral Coefficients, and a classification part based on the minimum distance rule. Two types of channel distortion were investigated: • Convolutional (or lowpass filtering) effects • Addition of white Gaussian noise Three different methods of channel compensation were tested: • Cepstral Mean Subtraction (CMS) • RelAtive SpecTrAl (RASTA) Processing • Constant Modulus Algorithm (CMA) The results from the experiments showed that for both CMS and RASTA processing that filtering at low cutoff frequencies, (3 or 4 kHz), produced improvements in the average speaker recognition rates compared to speech with no compensation. The levels of improvement due to RASTA processing were higher than the levels achieved due to the CMS method. Neither the CMS or RASTA methods were able to improve accuracy of the speaker recognition system for cutoff frequencies of 5 kHz, 6 kHz or 7 kHz. In the case of noisy speech all methods analysed were able to compensate for high SNR of 40 dB and 30 dB and only RASTA processing was able to compensate and improve the average recognition rate for speech corrupted with a high level of noise (SNR of 20 dB and 10 dB).

The multiple constant multiplication (MCM) operation is a fundamental operation in digital signal processing (DSP) and digital image processing (DIP). Examples of the MCM are in finite impulse response (FIR) and infinite impulse response (IIR) filters, matrix multiplication, and transforms. The aim of this work is minimizing the complexity of the MCM operation using common subexpression elimination (CSE) technique and redundant number representations. The CSE technique searches and eliminates common digit patterns (subexpressions) among MCM coefficients. More common subexpressions can be found by representing the MCM coefficients using redundant number representations. A CSE algorithm is proposed that works on a type of redundant numbers called the zero-dominant set (ZDS). The ZDS is an extension over the representations of minimum number of non-zero digits called minimum Hamming weight (MHW). Using the ZDS improves CSE algorithms' performance as compared with using the MHW representations. The disadvantage of using the ZDS is it increases the possibility of overlapping patterns (digit collisions). In this case, one or more digits are shared between a number of patterns. Eliminating a pattern results in losing other patterns because of eliminating the common digits. A pattern preservation algorithm (PPA) is developed to resolve the overlapping patterns in the representations. A tree and graph encoders are proposed to generate a larger space of number representations. The algorithms generate redundant representations of a value for a given digit set, radix, and wordlength. The tree encoder is modified to search for common subexpressions simultaneously with generating of the representation tree. A complexity measure is proposed to compare between the subexpressions at each node. The algorithm terminates generating the rest of the representation tree when it finds subexpressions with maximum sharing. This reduces the search space while minimizes the hardware complexity. A combinatoric model of the MCM problem is proposed in this work. The model is obtained by enumerating all the possible solutions of the MCM that resemble a graph called the demand graph. Arc routing on this graph gives the solutions of the MCM problem. A similar arc routing is found in the capacitated arc routing such as the winter salting problem. Ant colony optimization (ACO) meta-heuristics is proposed to traverse the demand graph. The ACO is simulated on a PC using Python programming language. This is to verify the model correctness and the work of the ACO. A parallel simulation of the ACO is carried out on a multi-core super computer using C++ boost graph library.

Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms.

Please read the abstract in the section 00front of this document
Dissertation (M Eng (Electronic Engineering))--University of Pretoria, 2006.
Electrical, Electronic and Computer Engineering
unrestricted

碩士
國立交通大學
電子工程系
90
Blind equalizers have long been employed to recover the distorted signal over ISI channel with AWGN noise. Among the many blind algorithms, constant modulus algorithm (CMA) is the most frequently employed adaptation algorithm in blind equalizers. In this thesis, we consider the applicability of such equalizers to the EN300429 DVB system using QAM modulation technique. Specifically, the effects of several algorithms for blind equalization are discussed and compared. Computer simulation results indicate that the performances of blind equalizers using SGA algorithm, one variant of the CMA, is the best approach for improving convergence speed and reducing steady state error. Also, the blind equalizers for DPASK modulation scheme can achieve similar convergence behaviors, if it is employed in DVB systems.

碩士
國立臺灣科技大學
電機工程系
101
In high-speed wireline communications, to reduce frequency-dependent channel loss is an important issue. The equalizer is an effective solution to resolve the frequency- dependent signal attenuation. This thesis proposed an on-chip constant-modulus-algorithm (CMA) -based Feed-Forward equalizer (FFE) to overcome this problem. Since CMA is a blind equalization method that does not need training sequence, the adaptive mechanism can be completely implemented on chip. This thesis proposed a constant-modulus-algorithm-based Feed-Forward equalizer that compensates the cable loss for 5 Gb/s USB 3.0 application. The CMA-based FFE chip was realized in TSMC 90 nm CMOS process. The power consumption of equalizer is 10.45 mW under 1.2 V supply voltage. The total chip area is 0.45 mm2 with pads, and the core area is 0.043 mm2. In post layout simulations, the proposed equalizer has the ability to compensate the cable loss for USB 3.0. In this thesis, we assumed a 1.8-meter and a 3-meter cable lines in simulations. The compensated cable loss are 11 dB (for the 1.8 m cable) and 16 dB (for the 3 m cable) at Nyquist frequency, respectively. After simulating a transmission of three hundred thousand bits, we show that the equalizer can improve BER from 3.3e-6 to 0 for the 1.8-meter USB 3.0 cable line; for the 3-meter USB 3.0 cable, it can improve the BER from 0.5 to 0.

碩士
國立臺灣科技大學
電機工程系
101
In high speed wireline communications, the frequency-dependent channel loss is an important issue. The equalizer is an effective method to resolve the frequency- dependent signal attenuation problem in wireline communications. This thesis realizes an on-chip constant-modulus-algorithm(CMA)-based decision feedback equalizer (DFE) to overcome the problem. The CMA is a blind equalization method, so it does not need a training sequence. Thus, the adaptive mechanism can be completely implemented on chip. The wireline we consider in this thesis is the RG58A/U coaxial cable for 3.125 Gb/s Ethernet application. The CMA-based DFE chip was realized in TSMC 0.18 μm CMOS process. The equalizer consumed 42 mW power at 1.8 V supply. The chip area is 1.25 mm2. In post layout simulations, the proposed equalizer can compensate for a 12.23-dB channel loss at Nyquist frequency for a 15-meter RG58A/U cable with 5.6667e-5 BER. For a 20-meter RG58A/U cable with 16.75 dB loss at Nyquist frequency, the equalizer can improve the BER from 2.3871e-1 down to 1.6633e-3.

碩士
國立臺灣科技大學
電機工程系
102
In high-speed wireline communications, to reduce frequency-dependent channel loss is an important issue. The equalizer is an effective solution to resolve the frequency- dependent signal attenuation. This thesis proposed an on-chip constant-modulus-algorithm (CMA) -based Feed-Forward equalizer (FFE) to overcome this problem. Since CMA is a blind equalization method that does not need training sequence, the adaptive mechanism can be completely implemented on chip. This thesis proposed the constant-modulus-algorithm-based Feed-Forward equalizer that compensates the cable loss for 5 Gb/s USB 3.0 application. The CMA-based FFE chip was realized in TSMC 90 nm CMOS process. The power consumption of equalizer is 14.4 mW under 1.2 V supply voltage. The total chip area is 0.59 mm2 with pads, and the core area is 0.058 mm2. In post layout simulations, the proposed equalizer has the ability to compensate the cable loss for USB 3.0. In this thesis, we assumed a 3-meter lines in simulations. The compensated cable loss are 16 dB for the 3 m cable at Nyquist frequency, respectively. After simulating a transmission of three hundred thousand bits, we show that the equalizer can improve BER from 0.5 to 0 for the 3-meter USB 3.0 cable. In fact, the equalizer can not improve the BER from 0.5 down to 0.

碩士
國立中山大學
電機工程學系研究所
90
In this thesis, the problem of multiple access interference (MAI) suppression for the multi-carrier (MC) code division multiple access (CDMA) system, based on the wavelet-based (WB) multi-carrier modulation, associated with the combining process is investigated for Rayleigh fading channel. The main concern of this thesis is to derive a new scheme, based on the linearly constrained constant modulus (LCCM) criterion with the robust inverse QR decomposition (IQRD) recursive least squares (RLS) algorithm to improve the performance of the conventional MC-CDMA system with combining process. To verify the merits of the new algorithm, the effect due to imperfect channel parameters estimation and frequency offset are investigated. We show that the proposed robust LCCM IQRD-RLS algorithm outperforms the conventional LCCM-gradient algorithm [6], in terms of output SINR, improvement percentage index (IPI), and bit error rate (BER) for MAI suppression under channel mismatch environment. Also, the performance of the WB MC-CDMA system is superior to the one with conventional MC-CDMA system. It is more robust to the channel mismatch and frequency offset. Moreover, the WB MC-CDMA system with robust LCCM IQRD-RLS algorithm does have better performance over other conventional approaches, such as the LCCM-gradient algorithm, maximum ratio combining (MRC), blind adaptation algorithm and partitioned linear interference canceller (PLIC) approach with LMS algorithm, in terms of the capability of MAI suppression and bit error rate (BER).

碩士
中原大學
電子工程研究所
98
Twin-QPSK is a four transmitting antennas space-time coding system with the features of orthogonal, full diversity, and full code rate. Here, the blind equalization at the receiver is proceeded by using the Modified Constant Modulus Algorithm (MCMA) which can estimate the transmitting signal without the training sequence in the system. The simulation results show that the original transmitted signals can be estimated efficiently. Compared with semi-blind algorithm, this approach not only increases the efficiency of using bandwidth, but also reduces the complexity of the system.

碩士
國立中山大學
電機工程學系研究所
95
In this thesis, the problem of multiple access interference (MAI) suppression for the multi-carrier (MC) code division multiple access (CDMA) system, based on the multi-carrier modulation with modified Gaussian wavelet, associated with the combining process is investigated for Rayleigh fading channel. The main concern of this thesis is to derive a new scheme, based on the linearly constrained constant modulus (LCCM) criterion with the robust inverse QR decomposition (IQRD) recursive least squares (RLS) algorithm to improve the performance of the wavelet-based MC-CDMA system with combining process. To verify the merits of the new algorithm, the effect due to imperfect channel parameters estimation and near-far effect are investigated. We show that the proposed robust LCCM IQRD-RLS algorithm outperforms the conventional LCCM-gradient algorithm, in terms of output SINR, for MAI suppression under channel mismatch environment. Also, the performance of the modified Gaussian wavelet-based MC-CDMA system is superior to the one with wavelet-based MC-CDMA system. It is more robust to the channel mismatch and near-far effect. Moreover, the modified Gaussian wavelet-based MC-CDMA system with robust LCCM IQRD-RLS algorithm does have better performance over other conventional approaches, such as the LCCM-gradient algorithm, maximum ratio combining (MRC), and blind adaptation algorithm, in terms of the capability of MAI suppression and bit error rate (BER).

碩士
國立中山大學
電機工程學系研究所
95
The code division multiple access (CDMA) system implemented by the direct-sequence (DS) spread spectrum (SS) technique is one of the most promising multiplexing technologies for the wireless communications services. The SS communication adopts a technique of using much wider bandwidth necessary to transmit the information over the channel, and has been proposed for third generation broadband wireless access. The capacity and performance of the DS-CDMA system are mainly limited by the multiple access interference (MAI) and the inter-symbol-interference (ISI) caused by the multipath-fading channel. To circumvent the above-mentioned problems many adaptive multiuser detectors, for instance the minimum mean square error (MMSE) and the minimum output energy (MOE) criteria, subject to certain constraints, have been proposed. Since the LCMV criterion is the linearly constrained (LC) version of MOE, it is high sensitivity to the channel mismatch caused by the unreliable estimation. In order to deal with this problem, the LC constant modulus (LCCM) criterion was considered to avoid capturing the interfering user instead of the desired user when the power of interfering user is much higher than the desired user. In this thesis, based on the Min/Max criterion we propose a novel blind LCCM recursive least-square (RLS) algorithm, with the generalized side-lobe canceller (GSC) structure, named as the CM GSC-RLS algorithm, to effectively alleviate the effect of MAI and ISI for DS-CDMA receiver, for time-varying channel. Due to the variation of channel at the receiver, the desired user amplitude or power is not available and has to be estimated. To solve this problem, we propose a simple scheme to estimate the parameter of constant modulus, adaptively, associated with the CM GSC-RLS algorithm. With the new proposed algorithm, the amplitude variation of desired user, due to changing characteristics of channel, can be tracked, effectively. Thus, better performance achievement, in terms of output signal-to-interference-plus-noise ratio (SINR) and bit error rate (BER), over the conventional GSC-RLS algorithms can be expected.

碩士
國立中山大學
電機工程學系研究所
97
In this thesis, we present a new hybrid pre-coded direct-sequence code division multiple access (DS-CDMA) system framework that use the multiple-input multiple-output (MIMO) antennas along with Alamouti’s space-time block code (ST-BC). In the transmitter, the idea of hybrid pre-coded is exploited. It not only used to counteract the inter-symbol interference (ISI) introduced by the channel fading duo to multipath propagation but also very useful for exacting the phase of channel by appropriate design, which is not adopted in the conventional blind receiver. Under this structure, we propose a new blind adaptive MIMO-CDMA receiver based on the linearly constrained constant modulus (LCCM) criterion. To reduce the complexity of receiver design, framework of the generalized sidelobe canceller (GSC) associated with the recursive least square (RLS) algorithm is adopted for implementing the LCCM MIMO-CDMA receiver, and use gradient method to track the desired user’s amplitude, simultaneously. Via computer simulations, advantages of the proposed scheme will be verified. Compared to the conventional blind Capon receiver, we will show that the performance of the proposed scheme is more robust against inaccuracies in the acquisition of the desired user’s timing.

碩士
國立中山大學
電機工程學系研究所
91
The direct-sequence code division multiple access (DS-CDMA) is one of the significant techniques for wireless communication systems with multiple simultaneous transmissions. The main concern of this thesis is to propose a new linearly constrained constant modulus modified conjugate gradient (LCCM-MCG) adaptive filtering algorithm to deal with problem of channel mismatch associated with the multiple access interference (MAI) in DS-CDMA system over multipath fading channel. In fact, the adaptive filtering algorithm based on the CM criterion is known to be very attractive for the case when the channel parameters are not estimated perfectly. The proposed LCCM-MCG algorithm is derived based on the so-called generalized sidelobe canceller (GSC). It has the advantage of having better stability and less computational complexity compared with conventional recursive least-squares (RLS) algorithm, and can be used to achieve desired performance for multiuser RAKE receiver. Moreover, with the MCG algorithm it requires only one recursive iteration per incoming sample data for updating the weight vector, but still maintains performance comparable to the RLS algorithm. From computer simulation results, we show that the proposed LCCM-MCG algorithm has fast convergence rate and could be used to circumvent the effect due to channel mismatch. Also, the performance, in terms of bit error rate (BER), is quite close to the LCCM-RLS algorithm suggested in [18], and is superior to the stochastic gradient descent (SGD) algorithm proposed in [7].

碩士
國立中山大學
電機工程學系研究所
94
The code division multiple access (CDMA) system implemented by the direct-sequence (DS) spread spectrum (SS) technique is one of the most promising multiplexing technologies for wireless communications services. The SS communication adopts a technique of using much wider bandwidth necessary to transmit the information over the channel. In the DS-CDMA system, due to the inherent structure interference, referred to as the multiple access interference (MAI), the system performance might degrade. Next, for DS-CDMA systems over frequency-selective fading channels, the effect of inter symbol interference (ISI) will exist, such that a multiuser RAKE receiver has to be employed to combat the ISI as well as MAI. Since, in practical wireless communication environment, there may have several communication systems operated in the same area at the same time. In this thesis, we consider the environment of DS-CDMA systems, where the asynchronous narrow band interference (NBI) due to other systems is joined suddenly to the CDMA system. In general, when a system works in a stable state with adaptive detectors, a suddenly joined NBI signal will cause the system performance to be crash down. Under such circumstance, the existing conventional adaptive RAKE detectors may not be able to track well for the rapidly sudden changing NBI associated with the problems of ISI and MAI. It is known that the adaptive filtering algorithms, based on the sliding window linear constrained recursive least squares (SW LC-RLS), is very attractive to a violent changing environment. The main concern of this thesis is to propose a novel sliding window constant modulus RLS (SW CM-RLS) algorithm, based on the Min/max criterion, to deal with the NBI for DS-CDMA system over multipath channels. For simplicity and having less system complexity the generalized side-lobe canceller (GSC) structure is employed, and is referred to as the SW CM-GSC-RLS algorithm. The aim of the SW CM-GSC-RLS algorithm is used to alleviate the effect of NBI. It has the advantages of having faster convergence property and tracking ability, and can be applied to the environment in which the NBI is suddenly joined to the system under the effect of channel mismatch to achieve desired performance. At the end of this thesis, we extend the idea of the proposed algorithm to the space-time DS-CDMA RAKE receiver, in which the adaptive beamformer with temporal domain DS-CDMA receiver is employed. Via computer simulation results, we show that our new proposed schemes outperform the conventional CM GSC-RLS algorithm as well as the GSC-RLS algorithm (the so-called LCMV approach), in terms of mean square error of estimating channel impulse response, output signal to interference plus noise ratio and bit-error-rate.

碩士
國立中央大學
通訊工程研究所
97
The combination of multiple input and multiple output (MIMO) technology and orthogonal frequency division multiplexing (OFDM) to combat multipath and mobile channels is widely used in wireless communications. For example, in wireless network applications with limited number of pilots, channel tracking is an important scheme to deal with time-varying channels. Here, the Alamouti space-time block code is applied to a two-by-two MIMO OFDM system in which we explore a new channel tracking algorithm that can alternatively operate between the constant modulus algorithm (CMA) and the decision feedback algorithm based on the proposed mechanism. The proposed algorithm is also further verified in an intercarrier interference cancellation algorithm that can solve the time-varying channel with changed status even between two consecutive OFDM symbols. Simulation results show that the proposed algorithm can achieve better performance than the method employing only the CMA method or the decision feedback method.

In this thesis we investigate the problem of image restoration. The main focus of our research is to come up with novel algorithms and enhance existing techniques in order to deliver efficient and effective methodologies, applicable in real-time image restoration scenarios. Our research starts with a literature review, which identifies the gaps in existing techniques and helps us to come up with a novel classification on image restoration, which integrates and discusses more recent developments in the area of image restoration. With this novel classification, we identified three major areas which need our attention. The first developments relate to non-blind image restoration. The two mostly used techniques, namely deterministic linear algorithms and stochastic nonlinear algorithms are compared and contrasted. Under deterministic linear algorithms, we develop a class of more effective novel quadratic linear regularization models, which outperform the existing linear regularization models. In addition, by looking in a new perspective, we evaluate and compare the performance of deterministic and stochastic restoration algorithms and explore the validity of the performance claims made so far on those algorithms. Further, we critically challenge the ne- cessity of some complex mechanisms in Maximum A Posteriori (MAP) technique under stochastic image deconvolution algorithms. The next developments are focussed in blind image restoration, which is claimed to be more challenging. Constant Modulus Algorithm (CMA) is one of the most popular, computationally simple, tested and best performing blind equalization algorithms in the signal processing domain. In our research, we extend the use of CMA in image restoration and develop a broad class of blind image deconvolution algorithms, in particular algorithms for blurring kernels with a separable property. These algorithms show significantly faster convergence than conventional algorithms. Although CMA method has a proven record in signal processing applications related to data communications systems, no research has been carried out to the investigation of the applicability of CMA for image restoration in practice. In filling this gap and taking into account the differences of signal processing in im- age processing and data communications contexts, we extend our research on the applicability of CMA deconvolution under the assumptions on the ground truth image properties. Through analyzing the main assumptions of ground truth image properties being zero-mean, independent and uniformly distributed, which char- acterize the convergence of CMA deconvolution, we develop a novel technique to overcome the effects of image source correlation based on segmentation and higher order moments of the source. Multichannel image restoration techniques recently gained much attention over the single channel image restoration due to the benefits of diversity and redundancy of the information between the channels. Exploiting these benefits in real time applications is often restricted due to the unavailability of multiple copies of the same image. In order to overcome this limitation, as the last area of our research, we develop a novel multichannel blind restoration model with a single image, which eliminates the constraint of the necessity of multiple copies of the blurred image. We consider this as a major contribution which could be extended to wider areas of research integrated with multiple disciplines such as demosaicing.

碩士
明新科技大學
工程管理研究所
92
This paper develops an operational strategy for the production scheduling of the module factory in thin film transistor liquid crystal display (TFT-LCD) manufacturing, where the module process involves a mass-customized production environment that depends on the availability of the key parts or components. How to meet a variety of designated materials requested by customers and how to cope with the quick response for confirmed orders will gradually become important issues for TFT-LCD industry. Basically, the traditional MRP (Material requirement planning) is such a planning approach based on preliminary assumptions of unlimited-capacity and fixed lead time, in which a capacity-adjusted effort is needed to meet the capacity constraints after MRP executed. Therefore, a constraint-based genetic algorithm (CBGA) simultaneously taking the designated material and available capacity constraints into account is developed for the purpose of minimizing earliness, tardiness, makespan, and flow time. Herein a factorial experiment design is used to evaluate the performance differences between the CBGA with two traditional dispatching rules, FS/EDD and BS/LDD. It has been shown that the performance obtained by CBGA is superior to those heuristics.