18 research outputs found

    Autoregressive models for text independent speaker identification in noisy environments

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    The closed-set speaker identification problem is defined as the search within a set of persons for the speaker of a certain utterance. It is reported that the Gaussian mixture model (GMM) classifier achieves very high classification accuracies (in the range 95% - 100%) when both the training and testing utterances are recorded in sound proof studio, i.e., there is neither additive noise nor spectral distortion to the speech signals. However, in real life applications, speech is usually corrupted by noise and band-limitation. Moreover, there is a mismatch between the recording conditions of the training and testing environments. As a result, the classification accuracy of GMM-based systems deteriorates significantly. In this thesis, we propose a two-step procedure for improving the speaker identification performance under noisy environment. In the first step, we introduce a new classifier: vector autoregressive Gaussian mixture (VARGM) model. Unlike the GMM, the new classifier models correlations between successive feature vectors. We also integrate the proposed method into the framework of the universal background model (UBM). In addition, we develop the learning procedure according to the maximum likelihood (ML) criterion. Based on a thorough experimental evaluation, the proposed method achieves an improvement of 3 to 5% in the identification accuracy. In the second step, we propose a new compensation technique based on the generalized maximum likelihood (GML) decision rule. In particular, we assume a general form for the distribution of the noise-corrupted utterances, which contains two types of parameters: clean speech-related parameters and noise-related parameters. While the clean speech related parameters are estimated during the training phase, the noise related parameters are estimated from the corrupted speech in the testing phase. We applied the proposed method to utterances of 50 speakers selected from the TIMIT database, artificially corrupted by convolutive and additive noise. The signal to noise ratio (SNR) varies from 0 to 20 dB. Simulation results reveal that the proposed method achieves good robustness against variation in the SNR. For utterances corrupted by covolutive noise, the improvement in the classification accuracy ranges from 70% for SNR = 0 dB to around 4% for SNR = 10dB, compared to the standard ML decision rule. For utterances corrupted by additive noise, the improvement in the classification accuracy ranges from 1% to 10% for SNRs ranging from 0 to 20 dB. The proposed VARGM classifier is also applied to the speech emotion classification problem. In particular, we use the Berlin emotional speech database to validate the classification performance of the proposed VARGM classifier. The proposed technique provides a classification accuracy of 76% versus 71% for the hidden Markov model, 67% for the k-nearest neighbors, 55% for feed-forward neural networks. The model gives also better discrimination between high-arousal emotions (joy, anger, fear), low arousal emotions (sadness, boredom), and neutral emotions than the HMM. Another interesting application of the VARGM model is the blind equalization of multi input multiple output (MIMO) communication channels. Based on VARGM modeling of MIMO channels, we propose a four-step equalization procedure. First, the received data vectors are fitted into a VARGM model using the expectation maximization (EM) algorithm. The constructed VARGM model is then used to filter the received data. A Baysian decision rule is then applied to identify the transmitted symbols up to a permutation and phase ambiguities, which are finally resolved using a small training sequence. Moreover, we propose a fast and easily implementable model order selection technique. The new equalization algorithm is compared to the whitening method and found to provide less symbol error probability. The proposed technique is also applied to frequency-flat slow fading channels and found to provide a more accurate estimate of the channel response than that provided by the blind de-convolution exploiting channel encoding (BDCC) method and at a higher information rate

    MMSE equalizers and precoders in turbo equalization.

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    Thesis (M.Sc.Eng.)-University of Natal, Durban, 2003.Transmission of digital information through a wireless channel with resolvable multipaths or a bandwidth limited channel results in intersymbol interference (1SI) among a number of adjacent symbols. The design of an equalizer is thus important to combat the ISI problem for these types of channels and hence provides reliable communication. Channel coding is used to provide reliable data transmission by adding controlled redundancy to the data. Turbo equalization (TE) is the joint design of channel coding and equalization to approach the achievable uniform input information rate of an ISI channel. The main focus of this dissertation is to investigate the different TE techniques used for a static frequency selective additive white Gaussian noise (AWGN) channel. The extrinsic information transfer (EXIT) chart is used to analyse the iterative equalization/decoding process and to determine the minimum signal to noise ratio (SNR) in order to achieve convergence. The use of the Minimum Mean Square Error (MMSE) Linear Equalizer (LE) using a priori information has been shown to achieve the same performance compared with the optimal trellis based Maximum A Posterior (MAP) equalizer for long block lengths. Motivated by improving the performance of the MMSE LE, two equalization schemes are initially proposed: the MMSE Linear Equalizer with Extrinsic information Feedback (LE-EF (1) and (U)). A general structure for the MMSE LE, MMSE Decision Feedback Equalizer (DFE) and two MMSE LE-EF receivers, using a priori information is also presented. The EXIT chart is used to analyse the two proposed equalizers and their characteristics are compared to the existing MAP equalizer, MMSE LE and MMSE DFE. It is shown that the proposed MMSE LE-EF (1) does have an improved performance compared with the existing MMSE LE and approaches the MMSE Linear Equalizer with Perfect Extrinsic information Feedback (LE-PEF) only after a large number of iterations. For this reason the MMSE LE-EF is shown to suffer from the error propagation problem during the early iterations. A novel way to reduce the error propagation problem is proposed to further improve the performance of the MMSE LE-EF (I). The MAP equalizer was shown to offer a much improved performance over the MMSE equalizers, especially during the initial iterations. Motivated by using the good quality of the MAP equalizer during the early iterations and the hybrid MAP/MMSE LE-EF (l) is proposed in order to suppress the error propagation problem inherent in the MMSE LE-EF (I). The EXIT chart analysis reveals that the hybrid MAP/MMSE LE-EF (l) requires fewer iterations in order to achieve convergence relative to the MMSE LE-EF (l). Simulation results demonstrate that the hybrid MAP/MMSE LE-EF (I) has a superior performance compared to the MMSE LE-EF (I) as well as approaches the performance of both the MAP equalizer and MMSE LE-PEF at high SNRs, at the cost of increased complexity relative to the MMSE LEEF (I) receiver. The final part of this dissertation considers the use of precoders in a TE system. It was shown in the literature that a precoder drastically improves the system performance. Motivated by this, the EXIT chart is used to analyse the characteristics of four different precoders for long block lengths. It was shown that using a precoder results in a loss in mutual information during the initial equalization stage. However" we show by analysis and simulations that this phenomenon is not observed in the equalization of all precoded channels. The slope of the transfer function, relating to the MAP equalization of a precoded ISI channel (MEP), during the high input mutual information values is shown to play an important role in determining the convergence of precoded TE systems. Simulation results are presented to show how the precoders' weight affects the convergence of TE systems. The design of the hybrid MAP/MEP equalizer is also proposed. We also show that the EXIT chart can be used to compute the trellis code capacity of a precoded ISI channel

    Convergence of millimeter-wave and photonic interconnect systems for very-high-throughput digital communication applications

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    In the past, radio-frequency signals were commonly used for low-speed wireless electronic systems, and optical signals were used for multi-gigabit wired communication systems. However, as the emergence of new millimeter-wave technology introduces multi-gigabit transmission over a wireless radio-frequency channel, the borderline between radio-frequency and optical systems becomes blurred. As a result, there come ample opportunities to design and develop next-generation broadband systems to combine the advantages of these two technologies to overcome inherent limitations of various broadband end-to-end interconnect systems in signal generation, recovery, synchronization, and so on. For the transmission distances of a few centimeters to thousands of kilometers, the convergence of radio-frequency electronics and optics to build radio-over-fiber systems ushers in a new era of research for the upcoming very-high-throughput broadband services. Radio-over-fiber systems are believed to be the most promising solution to the backhaul transmission of the millimeter-wave wireless access networks, especially for the license-free, very-high-throughput 60-GHz band. Adopting radio-over-fiber systems in access or in-building networks can greatly extend the 60-GHz signal reach by using ultra-low loss optical fibers. However, such high frequency is difficult to generate in a straightforward way. In this dissertation, the novel techniques of homodyne and heterodyne optical-carrier suppressions for radio-over-fiber systems are investigated and various system architectures are designed to overcome these limitations of 60-GHz wireless access networks, bringing the popularization of multi-gigabit wireless networks to become closer to the reality. In addition to the advantages for the access networks, extremely high spectral efficiency, which is the most important parameter for long-haul networks, can be achieved by radio-over-fiber signal generation. As a result, the transmission performance of spectrally efficient radio-over-fiber signaling, including orthogonal frequency division multiplexing and orthogonal wavelength division multiplexing, is broadly and deeply investigated. On the other hand, radio-over-fiber is also used for the frequency synchronization that can resolve the performance limitation of wireless interconnect systems. A novel wireless interconnects assisted by radio-over-fiber subsystems is proposed in this dissertation. In conclusion, multiple advantageous facets of radio-over-fiber systems can be found in various levels of end-to-end interconnect systems. The rapid development of radio-over-fiber systems will quickly change the conventional appearance of modern communications.PhDCommittee Chair: Gee-Kung Chang; Committee Member: Bernard Kippelen; Committee Member: Shyh-Chiang Shen; Committee Member: Thomas K. Gaylord; Committee Member: Umakishore Ramachandra

    Synchronization algorithms and architectures for wireless OFDM systems

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    Orthogonal frequency division multiplexing (OFDM) is a multicarrier modulation technique that has become a viable method for wireless communication systems due to the high spectral efficiency, immunity to multipath distortion, and being flexible to integrate with other techniques. However, the high-peak-to-average power ratio and sensitivity to synchronization errors are the major drawbacks for OFDM systems. The algorithms and architectures for symbol timing and frequency synchronization have been addressed in this thesis because of their critical requirements in the development and implementation of wireless OFDM systems. For the frequency synchronization, two efficient carrier frequency offset (CFO) estimation methods based on the power and phase difference measurements between the subcarriers in consecutive OFDM symbols have been presented and the power difference measurement technique is mapped onto reconfigurable hardware architecture. The performance of the considered CFO estimators is investigated in the presence of timing uncertainty conditions. The power difference measurements approach is further investigated for timing synchronization in OFDM systems with constant modulus constellation. A new symbol timing estimator has been proposed by measuring the power difference either between adjacent subcarriers or the same subcarrier in consecutive OFDM symbols. The proposed timing metric has been realized in feedforward and feedback configurations, and different implementation strategies have been considered to enhance the performance and reduce the complexity. Recently, multiple-input multiple-output (MIMO) wireless communication systems have received considerable attention. Therefore, the proposed algorithms have also been extended for timing recovery and frequency synchronization in MIMO-OFDM systems. Unlike other techniques, the proposed timing and frequency synchronization architectures are totally blind in the sense that they do not require any information about the transmitted data, the channel state or the signal-to-noise-ratio (SNR). The proposed frequency synchronization architecture has low complexity because it can be implemented efficiently using the three points parameter estimation approach. The simulation results confirmed that the proposed algorithms provide accurate estimates for the synchronization parameters using a short observation window. In addition, the proposed synchronization techniques have demonstrated robust performance over frequency selective fading channels that significantly outperform other well-established methods which will in turn benefit the overall OFDM system performance. Furthermore, an architectural exploration for mapping the proposed frequency synchronization algorithm, in particular the CFO estimation based on the power difference measurements, on reconfigurable computing architecture has been investigated. The proposed reconfigurable parallel and multiplexed-stream architectures with different implementation alternatives have been simulated, verified and compared for field programmable gate array (FPGA) implementation using the Xilinx’s DSP design flow.EThOS - Electronic Theses Online ServiceMinistry of Higher Education and Scientific Research (MOHSR) of IraqGBUnited Kingdo

    Design of large polyphase filters in the Quadratic Residue Number System

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    I/Q Imbalance in Multiantenna Systems: Modeling, Analysis and RF-Aware Digital Beamforming

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    Wireless communications has experienced an unprecedented increase in data rates, numbers of active devices and selection of applications during recent years. However, this is expected to be just a start for future developments where a wireless connection is seen as a fundamental resource for almost any electrical device, no matter where and when it is operating. Since current radio technologies cannot provide such services with reasonable costs or even at all, a multitude of technological developments will be needed. One of the most important subjects, in addition to higher bandwidths and flexible network functionalities, is the exploitation of multiple antennas in base stations (BSs) as well as in user equipment (UEs). That kind of multiantenna communications can boost the capacity of an individual UE-BS link through spatial antenna multiplexing and increase the quality as well as robustness of the link via antenna diversity. Multiantenna technologies provide improvements also on the network level through spatial UE multiplexing and sophisticated interference management. Additionally, multiple antennas can provide savings in terms of the dissipated power since transmission and reception can be steered more efficiently in space, and thus power leakage to other directions is decreased. However, several issues need to be considered in order to get multiantenna technologies widely spread. First, antennas and the associated transceiver chains are required to be simple and implementable with low costs. Second, size of the antennas and transceivers need to be minimized. Finally, power consumption of the system must be kept under control. The importance of these requirements is even emphasized when considering massive multiple-input multiple-output (MIMO) systems consisting of devices equipped with tens or even hundreds of antennas.In this thesis, we consider multiantenna devices where the associated transceiver chains are implemented in such a way that the requirements above can be met. In particular, we focus on the direct-conversion transceiver principle which is seen as a promising radio architecture for multiantenna systems due to its low costs, small size, low power consumption and good flexibility. Whereas these aspects are very promising, direct-conversion transceivers have also some disadvantages and are vulnerable to certain imperfections in the analog radio frequency (RF) electronics in particular. Since the effects of these imperfections usually get even worse when optimizing costs of the devices, the scope of the thesis is on the effects and mitigation of one of the most severe RF imperfection, namely in-phase/quadrature (I/Q) imbalance.Contributions of the thesis can be split into two main themes. First of them is multiantenna narrowband beamforming under transmitter (TX) and receiver (RX) I/Q imbalances. We start by creating a model for the signals at the TX and RX, both under I/Q imbalances. Based on these models we derive analytical expressions for the antenna array radiation patterns and notice that I/Q imbalance distorts not only the signals but also the radiation characteristics of the array. After that, stemming from the nature of the distortion, we utilize widely-linear (WL) processing, where the signals and their complex conjugates are processed jointly, for the beamforming task under I/Q imbalance. Such WL processing with different kind of statistical and adaptive beamforming algorithms is finally shown to provide a flexible operation as well as distortion-free signals and radiation patterns when being under various I/Q imbalance schemes.The second theme extends the work to wideband systems utilizing orthogonal frequency-division multiplexing (OFDM)-based waveforms. The focus is on uplink communications and BS RX processing in a multiuser MIMO (MU-MIMO) scheme where spatial UE multiplexing is applied and further UE multiplexing takes place in frequency domain through the orthogonal frequency-division multiple access (OFDMA) principle. Moreover, we include the effects of external co-channel interference into our analysis in order to model the challenges in heterogeneous networks. We formulate a flexible signal model for a generic uplink scheme where I/Q imbalance occurs on both TX and RX sides. Based on the model, we analyze the signal distortion in frequency domain and develop augmented RX processing methods which process signals at mirror subcarrier pairs jointly. Additionally, the proposed augmented methods are numerically shown to outperform corresponding per-subcarrier method in terms of the instantaneous signal-to-interference-and-noise ratio (SINR). Finally, we address some practical aspects and conclude that the augmented processing principle is a promising tool for RX processing in multiantenna wideband systems under I/Q imbalance.The thesis provides important insight for development of future radio networks. In particular, the results can be used as such for implementing digital signal processing (DSP)-based RF impairment mitigation in real world transceivers. Moreover, the results can be used as a starting point for future research concerning, e.g., joint effects of multiple RF impairments and their mitigation in multiantenna systems. Overall, this thesis and the associated publications can help the communications society to reach the ambitious aim of flexible, low-cost and high performance radio networks in the future

    Temperature aware power optimization for multicore floating-point units

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    Advanced Signal Processing for MIMO-OFDM Receivers

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