In this thesis, we consider the joint design of transceivers for a multiple access Multiple Input and Multiple Output (MIMO) system having Inter-Symbol Interference (ISI) channels. The system we consider is equipped with the Minimum Mean Square Error (MMSE) Decision-Feedback (DF) detector. Traditionally, transmitter designs for this system have been based on constraints of either the transmission power or the signal-to-interference-and-noise ratio (SINR) for each user. Here, we explore a novel perspective and examine a transceiver design which is under a fixed sum Gaussian mutual information constraint and minimizes the arithmetic mean square error of the MMSE-decision feedback detection. For this optimization problem, a closed-form solution is obtained. We prove that the optimal solution is achieved if and only if the sum mutual information is uniformly distributed over each individual user per the number of its active subchannels; i.e., user mutual information uniform distribution. Meanwhile, the Gaussian mutual information of the current user under perfect feedback for all the previous users is uniformly distributed over each individual symbol within the block signal of the user; i.e., symbol mutual information uniform distribution. The user mutual information uniform distribution is attained by successively solving a series of inverse (dual) problems of maximizing single user throughput, while the symbol mutual information uniform distribution is maintained by using the equal diagonal QRS decomposition. We also show that such uniform decomposition, in addition to minimizing the arithmetic MSE of MMSE-decision feedback detection, also has another two optimality properties: (a) Both the optimal user-detection order and symbol-detection order are natural orders in terms of signal to interference and noise ratios. (b) The free-distance for the Maximum Likelihood (ML) detector has an asymptotic behavior when the sum Gaussian mutual information tends to large. / Thesis / Master of Applied Science (MASc)

In this paper, we propose a new method for noise robustness base on Gaussian Mixture Model (GMM), and the method we proposed can estimate the noise feature effectively and reduce noise effect by plain fashion, and we can retain the smoothing and continuity from original feature in this way. Compared to the traditional feature transformation method MMSE(Minimum Mean Square Error) which want to find a clean one, the different is that the method we proposed only need to fine noise feature or the margin of noise effect and subtract the noise to achieve more robustness effect than traditional methods. In the experiment method, the test data pass through the trained noise classifier to judge the noise type and SNR, and according to the result of classifier to choose the corresponding transformation model and generate the noise feature by this model, and then we can use different weight linear combination to generate noise feature, and finally apply simple subtraction to achieve noise reduction. In the experiment, we use AURORA 2.0 corpus to estimate noise robustness performance, and using traditional method can achieve 36:8% relative improvement than default, and the our method can achieve 52:5% relative improvement, and compared to the traditional method our method can attain 24:9% relative improvement.

Currently, the 3rd Generation Partnership Project (3GPP) standards body is working actively to specify Voice services over Adaptive Multi-user channels on One Slot (VAMOS), an enhanced transmission scheme to double the voice service capacity in existing Global System for Mobile communications (GSM) system. Capacity increase is achieved by multiplexing two users in the same timeslot within the same radio frequency channel. With this new transmission scheme, several characteristics of VAMOS downlink signals can be taken into account in mobile station equalizer design. Firstly, the base station maps a pair of bits from the two VAMOS users to a quaternary symbol whose I/Q amplitude ratio may vary burst by burst. When the ratio is not unity, the VAMOS downlink signal is improper because its pseudo-covariance does not vanish. Secondly, in the baseband modulation stage, the symbol sequence is processed by ??/2 progressive symbol rotation and linearized Gaussian minimum shift keying (LGMSK) pulse shaping. Hence, intersymbol interference (ISI) is introduced. Lastly, due to tight frequency reuse in most GSM networks today, mobile stations also experience co-channel interference (CCI) from other base stations transmitting various types of signals such as GMSK, 8 phase shift keying (8PSK), or VAMOS. In order to achieve network capacity increase, advanced equalizers in mobile stations are required to offer superior bit error rate (BER) performance in this challenging mobile radio system. Unlike uplink transmission where a base station is typically equipped with an antenna array to enhance the desired signal and suppress CCI, equalizer design in downlink direction is more challenging because most mobile stations have one antenna only. In the past decade, various single antenna interference cancellation (SAIC) solutions have been developed to mitigate the CCI effect. While these solutions can be straightforwardly reused to obtain acceptable performance in VAMOS, in this work a novel equalizer is proposed to achieve better BER performance by addressing the forementioned characteristics of VAMOS downlink signals. This equalizer consists of a widely linear multiple-input multiple-output (MIMO) minimum mean square error (MMSE) filter and a joint maximum likelihood sequence estimator (JMLSE). In the first stage, since the transmitted signal and the received signal may not be jointly proper, a widely linear filter is more effective in suppressing interference from other base stations plus background noise while preserving the two paired VAMOS users??? signal energy. In the next stage, further interference cancellation is achieved by jointly detecting the two users??? symbol sequences using JMLSE. Optimality of the proposed equalizer is justified by theoretical proof and simulation in this work.

Introdução O envelhecimento populacional é uma realidade no Equador e este fato resulta em maior prevalência dos problemas mais frequentes em idosos, dentre eles, a deterioração das funções cognitivas. Objetivo Avaliar a função cognitiva, prevalência e fatores de risco associados ao declínio cognitivo e demência em pessoas com mais de 65 anos em Cumbayá-Quito, Equador. Métodos Este é um estudo de observação transversal que foi realizado em adultos com mais de 65 anos de idade. O Mini Exame do Estado Mental (MMSE), o Dementia Screening Interview (AD8) e a Mini Avaliação Nutricional (MNA) foram utilizados para avaliar o estado cognitivo e os hábitos nutricionais dessa população. Resultados Um total de 144 pacientes (idade média 75,3; 77,1% mulheres) fizeram parte deste estudo; 40% dos pacientes apresentaram testes positivos (AD8 e MMSE) consistentes com comprometimento cognitivo, possível demência. A idade (p<0,01), a escolaridade inferior (p <0,01), acidente vascular cerebral (p <0,01), hemorragia intracerebral (p<0,01), diabetes mellitus (p<0,01) e desnutrição (p<0,01) foram riscos significativos para o comprometimento cognitivo. O exercício (p <0,03) e o consumo de álcool (p=0,02) foram fatores de risco protetores para o declínio cognitivo nessa população. Gênero, etnia, localização, traumatismo craniano, doença de Parkinson, colesterol alto, diabetes, infarto do miocárdio, doença da tireóide, depressão, ansiedade, história familiar de demência não foram associados ao declínio cognitivo nessa população. Conclusões A prevalência de comprometimento cognitivo e possível demência aos 65 anos é de 18-21% e aos 85 anos é de 54-60% em Cumbayá, Quito, Equador. Os principais fatores de risco para deficiência cognitiva nesta população são idade, educação, desnutrição, acidente vascular cerebral e diabetes mellitus. Os fatores protetores para o declínio cognitivo foram o exercício e possivelmente o consumo moderado de álcool. / Introduction Population aging is a reality in Ecuador and this fact results in a higher prevalence of the most frequent problems in the elderly, among them, the deterioration of cognitive functions. Objective To assess the cognitive function, prevalence, and risk factors associated with cognitive decline and dementia in people over 65 years of age in Cumbayá-Quito, Ecuador. Methods This is a cross-sectional observational study that was carried out in adults over 65 years of age. The Mini Mental Scale Examination (MMSE), Dementia Screening Interview (AD8) and Mini Nutritional Assessment (MNA) were used to assess the cognition status and nutritional habits of this population. Results A total 144 patients (mean age 75.3; 77.1% females) were part of this study; 40% of patients had positive tests (AD8 & MMSE) consistent with cognitive impairment, possible dementia. The age (p<0.01), lower school education (p<0.01), stroke (p<0.01), intracerebral hemorrhage (p<0.01), diabetes (p<0.01) and malnutrition (p<0.01), were significant risk factors for cognitive impairment. Exercise (p<0.03) and consumption of alcohol were a protective risk factor for cognitive decline in this population. Gender, ethnicity, location, head trauma, Parkinson disease, high cholesterol, diabetes, myocardial infarction, thyroid disease, depression, anxiety, family history of dementia were not associated with cognitive decline in this population. Conclusions The prevalence of cognitive impairment and possible dementia at the age of 65 years is 18-21% and at age 85 years is 54-60% in Cumbayá, Quito, Ecuador. The main risk factors for cognitive impairment in this population were age, education, malnutrition, stroke, and diabetes. Protective factors for cognitive decline were exercise and possibly modest consumption of alcohol.

Introdução O envelhecimento populacional é uma realidade no Equador e este fato resulta em maior prevalência dos problemas mais frequentes em idosos, dentre eles, a deterioração das funções cognitivas. Objetivo Avaliar a função cognitiva, prevalência e fatores de risco associados ao declínio cognitivo e demência em pessoas com mais de 65 anos em Cumbayá-Quito, Equador. Métodos Este é um estudo de observação transversal que foi realizado em adultos com mais de 65 anos de idade. O Mini Exame do Estado Mental (MMSE), o Dementia Screening Interview (AD8) e a Mini Avaliação Nutricional (MNA) foram utilizados para avaliar o estado cognitivo e os hábitos nutricionais dessa população. Resultados Um total de 144 pacientes (idade média 75,3; 77,1% mulheres) fizeram parte deste estudo; 40% dos pacientes apresentaram testes positivos (AD8 e MMSE) consistentes com comprometimento cognitivo, possível demência. A idade (p<0,01), a escolaridade inferior (p <0,01), acidente vascular cerebral (p <0,01), hemorragia intracerebral (p<0,01), diabetes mellitus (p<0,01) e desnutrição (p<0,01) foram riscos significativos para o comprometimento cognitivo. O exercício (p <0,03) e o consumo de álcool (p=0,02) foram fatores de risco protetores para o declínio cognitivo nessa população. Gênero, etnia, localização, traumatismo craniano, doença de Parkinson, colesterol alto, diabetes, infarto do miocárdio, doença da tireóide, depressão, ansiedade, história familiar de demência não foram associados ao declínio cognitivo nessa população. Conclusões A prevalência de comprometimento cognitivo e possível demência aos 65 anos é de 18-21% e aos 85 anos é de 54-60% em Cumbayá, Quito, Equador. Os principais fatores de risco para deficiência cognitiva nesta população são idade, educação, desnutrição, acidente vascular cerebral e diabetes mellitus. Os fatores protetores para o declínio cognitivo foram o exercício e possivelmente o consumo moderado de álcool. / Introduction Population aging is a reality in Ecuador and this fact results in a higher prevalence of the most frequent problems in the elderly, among them, the deterioration of cognitive functions. Objective To assess the cognitive function, prevalence, and risk factors associated with cognitive decline and dementia in people over 65 years of age in Cumbayá-Quito, Ecuador. Methods This is a cross-sectional observational study that was carried out in adults over 65 years of age. The Mini Mental Scale Examination (MMSE), Dementia Screening Interview (AD8) and Mini Nutritional Assessment (MNA) were used to assess the cognition status and nutritional habits of this population. Results A total 144 patients (mean age 75.3; 77.1% females) were part of this study; 40% of patients had positive tests (AD8 & MMSE) consistent with cognitive impairment, possible dementia. The age (p<0.01), lower school education (p<0.01), stroke (p<0.01), intracerebral hemorrhage (p<0.01), diabetes (p<0.01) and malnutrition (p<0.01), were significant risk factors for cognitive impairment. Exercise (p<0.03) and consumption of alcohol were a protective risk factor for cognitive decline in this population. Gender, ethnicity, location, head trauma, Parkinson disease, high cholesterol, diabetes, myocardial infarction, thyroid disease, depression, anxiety, family history of dementia were not associated with cognitive decline in this population. Conclusions The prevalence of cognitive impairment and possible dementia at the age of 65 years is 18-21% and at age 85 years is 54-60% in Cumbayá, Quito, Ecuador. The main risk factors for cognitive impairment in this population were age, education, malnutrition, stroke, and diabetes. Protective factors for cognitive decline were exercise and possibly modest consumption of alcohol.

<p> In this thesis, we consider a multiuser downlink OFDM system for which the channel state information ( CSI) is known to both the transmitter and the receiver. </p> <p> For such a system, we design an optimal precoder that minimizes the total mean square error (MSE) subject to a total power constraint for which a minimum MSE (MMSE) equalizer is employed. We show that, the MMSE precoder can be obtained by optimally allocating the subcarriers and optimally allocating the power. This problem can be solved by a two-stage process, in which we minimize the lower bound of the MSE to obtain the optimal power for each subcarrier, followed by seeking an optimal precoder to achieve this minimized lower bound. Specifically, our subcarrier allocation strategy states that, each subcarrier should be allocated to only one user that has the largest subchannel gain in that subcarrier. </p> <P> Moreover, based on this subcarrier allocation strategy, we perform an optimal power loading and design the corresponding optimal precoder that minimizes the average bit error rate (BER). Here, the MMSE equalizer is also employed. This optimization problem is solved by two stages. In the first stage, we derive the lower bound of the average BER and minimize this lower bound. After we employ the MMSE subcarrier allocation strategy, the optimal power loading problem can be efficiently solved by interior point methods. In order to reduce computation complexity, an alternative, efficient power loading method is proposed here, which is much more efficient when the number of subcarriers is large. In the second stage, to achieve the minimized lower bound, we seek a design of an optimal precoder. Simulation results show that for moderate to high signal-to-noise ratio (SNR), the performance of the minimum BER {MBER) precoder employed with the MMSE equalizer design is superior to several other design methods, including the MMSE precoder design. </p> / Thesis / Master of Applied Science (MASc)

This thesis focuses on the design and analysis of an optimal filter that is capable of making one-step-ahead prediction of a bandlimited signal while attenuating unwanted noise. First, the filter optimization based on the least mean-square-error criterion is presented. Then, an exact expression for the achievable minimum mean square error (MMSE) is derived with the aid of the Toeplitz form method and Szego theory. Based on this MMSE expression, the formulae for estimating the optimal filter¡¦s in-band prediction error and out-of-band noise attenuation are derived. Finally, the optimal filter is applied to sigma-delta modulation. It shows that the modulation performance and stability are intimately related to the filter performance and can be accurately estimated by the derived formulae.

Modern data analysis often involves a large number of variables, which gives rise to the problem of multicollinearity in regression models. It is well-known that in a linear model, when the design matrix X is nearly singular, then the ordinary least squares (OLS) estimator may perform poorly because of its numerical instability and large variance. To overcome this problem, many linear or nonlinear biased estimators are studied. In this work we consider a class of generalized shrunken least squares (GSLS) estimators that include many well-known linear biased estimators proposed in the literature. We compare these estimators under the mean square error and matrix mean square error criteria. Moreover, a simulation study and two numerical examples are used to illustrate some of the theoretical results.

Modern data analysis often involves a large number of variables, which gives rise to the problem of multicollinearity in regression models. It is well-known that in a linear model, when the design matrix X is nearly singular, then the ordinary least squares (OLS) estimator may perform poorly because of its numerical instability and large variance. To overcome this problem, many linear or nonlinear biased estimators are studied. In this work we consider a class of generalized shrunken least squares (GSLS) estimators that include many well-known linear biased estimators proposed in the literature. We compare these estimators under the mean square error and matrix mean square error criteria. Moreover, a simulation study and two numerical examples are used to illustrate some of the theoretical results.

No description available.