305 research outputs found

    Wireless multiuser communication systems: diversity receiver performance analysis, GSMuD design, and fading channel simulator

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    Multipath fading phenomenon is central to the design and analysis of wireless communication systems including multiuser systems. If untreated, the fading will corrupt the transmitted signal and often cause performance degradations such as increased communication error and decreased data rate, as compared to wireline channels with little or no multipath fading. On the other hand, this multipath fading phenomenon, if fully utilized, can actually lead to system designs that provide additional gains in system performance as compared to systems that experience non-fading channels.;The central question this thesis tries to answer is how to design and analyze a wireless multiuser system that takes advantage of the benefits the diversity multipath fading channel provides. Two particular techniques are discussed and analyzed in the first part of the thesis: quadrature amplitude modulation (QAM) and diversity receivers, including maximal ratio combining (MRC) and generalized selection combining (GSC). We consider the practical case of imperfect channel estimation (ICE) and develop a new decision variable (DV) of MRC receiver output for M-QAM. By deriving its moment generating function (MGF), we obtain the exact bit error rate (BER) performance under arbitrary correlated Rayleigh and Rician channels, with ICE. GSC provides a tradeoff between receiver complexity and performance. We study the effect of ICE on the GSC output effective SNR under generalized fading channels and obtain the exact BER results for M-QAM systems. The significance of this part lies in that these results provide system designers means to evaluate how different practical channel estimators and their parameters can affect the system\u27s performance and help them distribute system resources that can most effectively improve performance.;In the second part of the thesis, we look at a new diversity technique unique to multiuser systems under multipath fading channels: the multiuser diversity. We devise a generalized selection multiuser diversity (GSMuD) scheme for the practical CDMA downlink systems, where users are selected for transmission based on their respective channel qualities. We include the effect of ICE in the design and analysis of GSMuD. Based on the marginal distribution of the ranked user signal-noise ratios (SNRs), we develop a practical adaptive modulation and coding (AMC) scheme and equal power allocation scheme and statistical optimal 1-D and 2-D power allocation schemes, to fully exploit the available multiuser diversity. We use the convex optimization procedures to obtain the 1-D and 2-D power allocation algorithms, which distribute the total system power in the waterfilling fashion alone the user (1-D) or both user and time (2-D) for the power-limited and energy-limited system respectively. We also propose a normalized SNR based GSMuD scheme where user access fairness issues are explicitly addressed. We address various fairness-related performance metrics such as the user\u27s average access probability (AAP), average access time (AAT), and average wait time (AWT) in the absolute- and normalized-SNR based GSMuD. These metrics are useful for system designers to determine parameters such as optimal packet size and delay constraints.;We observe that Nakakagami-m fading channel model is widely applied to model the real world multipath fading channels of different severity. In the last part of the thesis, we propose a Nakagami-m channel simulator that can generate accurate channel coefficients that follow the Nakagami-m model, with independent quadrature parts, accurate phase distribution and arbitrary auto-correlation property. We demonstrate that the proposed simulator can be extremely useful in simulations involving Nakagami-m fading channel models, evident from the numerous simulation results obtained in earlier parts of the thesis where the fading channel coefficients are generated using this proposed simulator

    Doctor of Philosophy

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    dissertationMultiple-input and multiple-output (MIMO) technique has emerged as a key feature for future generations of wireless communication systems. It increases the channel capacity proportionate to the minimum number of transmit and receive antennas. This dissertation addresses the receiver design for high-rate MIMO communications in at fading environments. The emphasis of the thesis is on the cases where channel state information (CSI) is not available and thus, clever channel estimation algorithms have to be developed to bene t from the maximum available channel capacity. The thesis makes four distinct novel contributions. First, we note that the conventional MCMC-MIMO detector presented in the prior work may deteriorate as SNR increases. We suggest and show through computer simulations that this problem to a great extent can be solved by initializing the MCMC detector with regulated states which are found through linear detectors. We also introduce the novel concept of staged-MCMC in a turbo receiver, where we start the detection process at a lower complexity and increase complexity only if the data could not be correctly detected in the present stage of data detection. Second, we note that in high-rate MIMO communications, joint data detection and channel estimation poses new challenges when a turbo loop is used to improve the quality of the estimated channel and the detected data. Erroneous detected data may propagate in the turbo loop and, thus, degrade the performance of the receiver signi cantly. This is referred to as error propagation. We propose a novel receiver that decorrelates channel estimation and the detected data to avoid the detrimental e ect of error propagation. Third, the dissertation studies joint channel estimation and MIMO detection over a continuously time-varying channel and proposes a new dual-layer channel estimator to overcome the complexity of optimal channel estimators. The proposed dual-layer channel estimator reduces the complexity of the MIMO detector with optimal channel estimator by an order of magnitude at a cost of a negligible performance degradation, on the order of 0.1 to 0.2 dB. The fourth contribution of this dissertation is to note that the Wiener ltering techniques that are discussed in this dissertation and elsewhere in the literature assume that channel (time-varying) statistics are available. We propose a new method that estimates such statistics using the coarse channel estimates obtained through pilot symbols. The dissertation also makes an additional contribution revealing di erences between the MCMC-MIMO and LMMSE-MIMO detectors. We nd that under the realistic condition where CSI has to be estimated, hence the available channel estimate will be noisy, the MCMC-MIMO detector outperforms the LMMSE-MIMO detector with a signi cant margin

    Probabilistic Structural Analysis Methods (PSAM) for Select Space Propulsion System Components

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    Probabilistic Structural Analysis Methods (PSAM) are described for the probabilistic structural analysis of engine components for current and future space propulsion systems. Components for these systems are subjected to stochastic thermomechanical launch loads. Uncertainties or randomness also occurs in material properties, structural geometry, and boundary conditions. Material property stochasticity, such as in modulus of elasticity or yield strength, exists in every structure and is a consequence of variations in material composition and manufacturing processes. Procedures are outlined for computing the probabilistic structural response or reliability of the structural components. The response variables include static or dynamic deflections, strains, and stresses at one or several locations, natural frequencies, fatigue or creep life, etc. Sample cases illustrates how the PSAM methods and codes simulate input uncertainties and compute probabilistic response or reliability using a finite element model with probabilistic methods

    On space-time trellis codes over rapid fading channels with channel estimation

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    Ph.DDOCTOR OF PHILOSOPH

    Scalable large margin pairwise learning algorithms

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    2019 Summer.Includes bibliographical references.Classification is a major task in machine learning and data mining applications. Many of these applications involve building a classification model using a large volume of imbalanced data. In such an imbalanced learning scenario, the area under the ROC curve (AUC) has proven to be a reliable performance measure to evaluate a classifier. Therefore, it is desirable to develop scalable learning algorithms that maximize the AUC metric directly. The kernelized AUC maximization machines have established a superior generalization ability compared to linear AUC machines. However, the computational cost of the kernelized machines hinders their scalability. To address this problem, we propose a large-scale nonlinear AUC maximization algorithm that learns a batch linear classifier on approximate feature space computed via the k-means Nyström method. The proposed algorithm is shown empirically to achieve comparable AUC classification performance or even better than the kernel AUC machines, while its training time is faster by several orders of magnitude. However, the computational complexity of the linear batch model compromises its scalability when training sizable datasets. Hence, we develop a second-order online AUC maximization algorithms based on a confidence-weighted model. The proposed algorithms exploit the second-order information to improve the convergence rate and implement a fixed-size buffer to address the multivariate nature of the AUC objective function. We also extend our online linear algorithms to consider an approximate feature map constructed using random Fourier features in an online setting. The results show that our proposed algorithms outperform or are at least comparable to the competing online AUC maximization methods. Despite their scalability, we notice that online first and second-order AUC maximization methods are prone to suboptimal convergence. This can be attributed to the limitation of the hypothesis space. A potential improvement can be attained by learning stochastic online variants. However, the vanilla stochastic methods also suffer from slow convergence because of the high variance introduced by the stochastic process. We address the problem of slow convergence by developing a fast convergence stochastic AUC maximization algorithm. The proposed stochastic algorithm is accelerated using a unique combination of scheduled regularization update and scheduled averaging. The experimental results show that the proposed algorithm performs better than the state-of-the-art online and stochastic AUC maximization methods in terms of AUC classification accuracy. Moreover, we develop a proximal variant of our accelerated stochastic AUC maximization algorithm. The proposed method applies the proximal operator to the hinge loss function. Therefore, it evaluates the gradient of the loss function at the approximated weight vector. Experiments on several benchmark datasets show that our proximal algorithm converges to the optimal solution faster than the previous AUC maximization algorithms

    Resource Allocation and Performance Analysis for Multiuser Video Transmission over Doubly Selective Channels

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    We consider an uplink multicarrier system with multiple video users who want to send compressed video data to the base station. In the time domain, we model the time varying channel using Jakes’ model, and in the frequency domain, each subcarrier is assumed to be independently fading. The video is scalably coded in units of group of pictures (GOP), and users have different video rate distortion (RD) functions. At the beginning of the GOP, the base station collects both the RD information and instantaneous channel state information (CSI) for subcarrier allocation purposes. We design a cross layer resource allocation algorithm to assign subcarriers to the users based on both the demand of the video and the quality of the channel. Once the resource allocation decision is made, the users then periodically adapt the modulation format of the subcarriers allocated according to the evolution of the CSI for the duration of the GOP. We show that our cross layer resource allocation robustly outperforms two baseline algorithms, each of which uses only one layer of information for resource allocation

    The Generation and Control of Ultrasonic Waves in Nonlinear Media

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    The objective of this thesis is to utilise modern open-design ultrasound research platforms to develop new and advance several existing techniques that incorporate nonlinear phenomena. Acoustically, nonlinearity refers to changes in speed of sound, attenuation or elasticity that vary with frequency, temperature or pressure. These effects cannot be linearised by the wave equation and require fluid dynamics and elasticity equations to be fully understood. While this is a hindrance and source of error in many areas of ultrasound such as high-intensity focused ultrasound (HIFU) and medical imaging, nonlinearities do have uses in non-destructive guided wave (GW) testing. These effects are influenced greatly by the transducer surface pressure, and so precise control of the excitation is necessary to achieve the desired nonlinear effect, if any, in the medium. In this thesis, aided by the use of two new research platforms, several new ultrasound techniques were developed. It was shown the frequency content in the electrical waveform is pertinent and so distortion must be minimised. This requirement conflicts with several hardware limitations, however. Accordingly, a genetic algorithm was applied to find novel switched waveform designs. It was found to achieve a 2% granularity in amplitude control with harmonic reduction, where existing waveform designs could not produce any. This fine amplitude control is a requirement for array applications. Following this, a technique to control the direction of GWs without knowledge of the waveguide was devised. Recordings of a propagating GW, induced by the first element of an array transducer, were re-transmitted in a recursive fashion. The effect was that the transducer's transmissions constructively interfered with the transverse wave, causing most of the guided wave energy to travel in the direction of the transducer's spatial influence. Experimental results show a 34 dB enhancement in one direction compared with the other. GWs were then applied to bone for two purposes: for assessment of osteoporosis and for measurement of skull properties to assist transcranial therapy. It was shown that existing methods for obtaining dispersion curves are ineffectual due to limitations in the available sampling area. A signal processing scheme was devised to temporally align transverse dispersive waves so that beamforming style techniques could be applied to prove or disprove the existence of certain modes. The technique in combination with multiplication was applied to numerical, ex vivo and in vivo experiments. It was found to improve the contrast of the higher order modes. The technique could improve the reliability of osteoporosis diagnosis with ultrasound, but may also prove useful for acquiring dispersion images in NDT. Numerically the technique was shown to improve the S3 and A3 mode intensity by 6 dB and 13 dB respectively compared with an existing Fourier method. In skull, a relationship was found between the curved therapeutic array geometry and the delay profile necessary to form GWs in skull. Several numerical models were tested and it was shown that the thickness could be obtained from the group velocity. The estimated maximum error using this technique was 0.2 mm. Since the data is co-registered with the therapeutic elements, this method could be used to improve the accuracy of thermal treatments in the brain. Finally, the application of switched excitation for HIFU was considered. To improve on cost, efficiency and size, alternative excitation methods have the potential to replace the linear amplifier circuitry currently used in HIFU. In this final study, harmonic reduction pulse width modulation (HRPWM) was proposed as an algorithmic solution to the design of switched waveforms. Its appropriateness for HIFU was assessed by design of a high power 5 level unfiltered amplifier and subsequent thermal-only lesioning of ex vivo chicken breast. HRPWM produced symmetric, thermal-only lesions that were the same size as their linear amplifier equivalents (p > 0.05). These results demonstrate that HRPWM can minimise HIFU drive circuity size without the need for filters to remove harmonics or adjustable power supplies to achieve array apodisation. Overall it has been shown in this thesis that precise control of the nonlinear wave phenomena can be afforded when using open-platform ultrasound research hardware. The methods described within may reduce the cost and increase the efficacy of future commercial systems

    An SDE for Modeling SAM: Theory and Insights

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    We study the SAM (Sharpness-Aware Minimization) optimizer which has recently attracted a lot of interest due to its increased performance over more classical variants of stochastic gradient descent. Our main contribution is the derivation of continuous-time models (in the form of SDEs) for SAM and two of its variants, both for the full-batch and mini-batch settings. We demonstrate that these SDEs are rigorous approximations of the real discrete-time algorithms (in a weak sense, scaling linearly with the learning rate). Using these models, we then offer an explanation of why SAM prefers flat minima over sharp ones~--~by showing that it minimizes an implicitly regularized loss with a Hessian-dependent noise structure. Finally, we prove that SAM is attracted to saddle points under some realistic conditions. Our theoretical results are supported by detailed experiments.Comment: Accepted at ICML 2023 (Poster

    Structural Integrity and Durability of Reusable Space Propulsion Systems

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    A two-day conference on the structural integrity and durability of reusable space propulsion systems was held on 14 to 15 May 1991 at the NASA Lewis Research Center. Presentations were made by industry, university, and government researchers organized into four sessions: (1) aerothermodynamic loads; (2) instrumentation; (3) fatigue, fracture, and constitutive modeling; and (4) structural dynamics. The principle objectives were to disseminate research results and future plans in each of four areas. This publication contains extended abstracts and the visual material presented during the conference. Particular emphasis is placed on the Space Shuttle Main Engine (SSME) and the SSME turbopump

    On channel estimation for mobile WiMAX

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    In mobile communication channels information symbols are transmitted through a communication channel that is prone to fading and multipath propagation. At the receiver, the effect of multipath propagation is reduced by a process called channel equalization. Channel equalization relies on an accurate estimate of the channel state information (CSI). This estimate is obtained using a channel estimation algorithm. Mobile WiMAX is a recently released technology that makes use of an orthogonal frequency division multiplexing (OFDM) based physical layer to transmit information over a wireless communication channel. In this dissertation, frequency and time domain channel estimation methods typically used in classical OFDM systems, using block and comb type pilot insertion schemes, were analyzed and adopted for mobile WiMAX. Least squares (LS) and linear minimum mean square error (LMMSE) channel estimation methods were considered in the case of block type pilot insertion. In the case of comb type pilot insertion, piecewise constant, linear, spline cubic as well as discrete Wiener interpolation methods were considered. A mobile WiMAX simulation platform was developed as part of the dissertation to evaluate and compare the performance of these different channel estimation methods. It was found that the performance of the channel estimation methods, applied to a real world mobile WiMAX simulation platform, conforms to the expected performance of the corresponding classical OFDM channel estimation methods found in literature.Dissertation (MEng)--University of Pretoria, 2009.Electrical, Electronic and Computer Engineeringunrestricte
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