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This paper describes the dynamic overmodulation strategies for fast torque control of the high-saliency-ratio ac motor. For the high-saliency-ratio ac motor, the dynamic control of both d- and q-axes currents is required for fast torque control with optimal efficiency. However, in transient operation, the d- and q-axes current regulators are easily saturated even at low speed because the stator inductance is designed large enough to generate the desired reluctance torque. With the conventional overmodulation strategies, the current regulation performance degrades severely compared to a nonsalient motor. In this paper, the drawbacks of the conventional overmodulation strategies are investigated and a dynamic overmodulation strategy is proposed to improve the current response to fast transients. For the effective implementation of the strategy, a practical algorithm is also presented. The performance of the proposed strategy is con- firmed by computer simulation and experiment with a 3.75-kW axially laminated synchronous reluctance motor and an interior Permanent-magnet synchronous motor for 42-V integrated starter-generator applications. [ABSTRACT FROM AUTHOR]

For coherent detection, block-coded modulation is a bandwidth efficient scheme. In this paper, we propose theorems about the error performance of block-coded modulation using Mary phase-shift keying (MPSK) for noncoherent detection. Based on these theorems, we propose a novel block-coded modulation scheme for noncoherent detection called noncoherent block-coded MPSK. The proposed scheme provides flexible designs of noncoherent block codes with different code rate, block length and error performance. Good noncoherent block codes can be easily obtained by properly choosing binary linear block codes as the component codes. Moreover, noncoherent block codes of this new scheme can be decoded by multistage decoding, which has the advantage of low complexity and satisfactory error performance. In this paper, two algorithms of multistage decoding for noncoherent detection are proposed as welt. The error performance of some designed codes and decoding algorithms is verified by computer simulation. [ABSTRACT FROM AUTHOR]

The wavelet transform, the S-transform, the Gabor transform, and the Wigner distribution function are popular techniques for power quality (PQ) analysis in electrical power systems. They are mainly used to identify power harmonics and power disturbances and to estimate power quantities in the presence of nonstationary power components such as root-mean-square values and total harmonic distortions. Recently, the Hilbert–Huang transform has been also used in PQ analysis. These techniques have proven to be useful in PQ analysis; however, their performances depend on the types of PQ events. In this paper, a novel frequency-shifting wavelet decomposition via the Hilbert transform is introduced for PQ analysis. The proposed algorithm overcomes the spectra leakage problem in the discrete wavelet packet transform and can be used for estimating power quantities accurately and for detecting flickers. The effectiveness of the proposed algorithm was verified by computer simulations and experimental tests. [ABSTRACT FROM PUBLISHER]

Driving simulators are increasingly being used for driver evaluation and/or education. In this paper, we describe the design and the modeling aspects of a 2-degree-of-freedom (2-DOF) low-cost motion platform allowing the rendering of the longitudinal and yaw movements. This prototype will be used to study various configurations of motion rendering and the impact of these variants on controllability and simulator sickness. The whole motion platform is considered as two coupled systems that are linked mechanically. The first system consists of a motorized rail for the longitudinal movement, which is mounted on top of the second system, which is a motorized turret allowing rotation of the platform. We present the platform mechanics and a number of experimental studies that have been carried out to obtain a characterization of the platform capabilities and frequency responses, as well as to assess platform performance in a classical drive operation. First conclusions and directions of future work are presented. [ABSTRACT FROM PUBLISHER]

This paper discusses a self-consistent set of modern computational concepts providing an effective approach to the circuit-level harmonic-balance (HB) simulation of nonlinear microwave systems of complex topology. The system is automatically split into the interconnection of a near-optimal number of nonlinear blocks at run time. The resulting structure is then exploited by the domain-partitioning concept. A block-wise constant spectrum is used rather than a common spectrum by considering for each block only the set of spectral lines that are relevant to its electrical function, which leads to a very significant reduction in the number of problem unknowns. System simulation under digitally modulated RF drive is reduced to a sequence of modified multitone HB analyses that are backward coupled through the envelope dynamics. Besides providing high numerical efficiency, this set of techniques opens the way to an effective co-simulation of RF and baseband transceiver sections. [ABSTRACT FROM AUTHOR]

An iterative receiver for a multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system is considered to jointly decode the transmitted bits and estimate the channel state. The receiver consists of a list detector, a turbo decoder, and a channel estimator that is based on the space-alternating generalized expectation-maximization (SAGE) algorithm. This paper proposes a way to improve the convergence of the iterative detection and decoding by using a priori information to also recalculate the candidate list, aside from the log-likelihood ratios (LLRs) of the coded bits. A new list parallel interference cancellation (PlC) detector is derived to approximate an a posteriori probability (APP) algorithm with reduced complexity and minimal losses of performance. Further- more, the organization of spectrally efficient decision-directed (DD) SAGE channel estimation under a constrained number of detector-decoder iterations is optimized by computer simulations, and the SAGE algorithm itself is modified for nonconstant envelope constellations. The list recalculation is shown to improve convergence. It is also shown that the list PlC detector with good initialization outperforms the K-best list sphere detector (LSD) in the case of small list sizes, whereas the complexities of the algorithms are of the same order. Despite the low preamble density and fast-fading channel, the proposed iterative receiver shows robust performance. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new robust congestion- control strategy for a differentiated-services (DiffServ) network. A sliding-mode-based variable structure control technique is utilized to design a congestion controller on the basis of a fluid flow model. The performance of our proposed scheme is then demonstrated on a DiffServ network. Our proposed algorithm is developed for an interconnected network as a hop-by-hop distributed-control approach. A formal analysis of the controlled network is conducted, where it is shown that the error dynamics of the overall time-delay-dependent system is ℒ∞ stable. Numerical simulations are provided to demonstrate the capabilities of our proposed methodology. [ABSTRACT FROM AUTHOR]

Finding the positions of nodes in an ad hoc wireless sensor network (WSN) with the use of the incomplete and noisy distance measurements between nodes as well as anchor position information is currently an important and challenging research topic. However, most WSN localization studies have considered that the anchor positions and the signal propagation speed are perfectly known which is not a valid assumption in the underwater and underground scenarios. In this paper, semi-definite programming (SDP) algorithms are devised for node localization in the presence of these uncertainties. The corresponding Cramér-Rao lower bound (CRLB) is also produced. Computer simulations are included to contrast the performance of the proposed algorithms with the conventional SDP method and CRLB. [ABSTRACT FROM AUTHOR]

Symbol timing offset (STO) can result in intersymbol interference (ISI) and a rotated phase which value is proportional to the subcarrier index at the FFT output in an OFDM receiver. In order to avoid ISI, the FFT window start position has to be put in advance of the estimated point obtained by coarse STO estimation algorithms. But a large number of forward-shift samples will deteriorate the estimation of data subcarrier channels requiring interpolation from pilot subcarrier channels due to the phase rotation caused by a residual STO. In this paper we analyze the influence of STO on channel interpolation and propose a new compensation method for channel correction with STO. From the performance analysis of simulation results in the DVB-T application, the new algorithm not only has a better performance but also is attractive in using a simple residual STO estimation method such that few pilots are required for fine STO estimation compared to conventional approaches. [ABSTRACT FROM AUTHOR]

The most popular algorithms for blind equalization are the constant-modulus algorithm (CMA) and the Shalvi-Wein- stein algorithm (SWA). It is well-known that SWA presents a higher convergence rate than CMA, at the expense of higher computational complexity. If the forgetting factor is not sufficiently close to one, if the initialization is distant from the optimal solution, or if the signal-to-noise ratio is low, SWA can converge to undesirable local minima or even diverge. In this paper, we show that divergence can be caused by an inconsistency in the nonlinear estimate of the transmitted signal, or (when the algorithm is implemented in finite precision) by the loss of positiveness of the estimate of the autocorrelation matrix, or by a combination of both. In order to avoid the first cause of divergence, we propose a dual-mode SWA. In the first mode of operation, the new algorithm works as SWA; in the second mode, it rejects inconsistent estimates of the transmitted signal. Assuming the persistence of excitation condition, we present a deterministic stability analysis of the new algorithm. To avoid the second cause of divergence, we propose a dual-mode lattice SWA, which is stable even in finite-precision arithmetic, and has a computational complexity that increases linearly with the number of adjustable equalizer coefficients. The good performance of the proposed algorithms is confirmed through numerical simulations. [ABSTRACT FROM AUTHOR]

This paper presents a modified decorrelated delay lock loop (MD-DLL) for synchronous direct-sequence code-division multiple-access (DS-CDMA) systems under multiuser environments. The structure of the MD-DLL is similar to that of a traditional delay lock loop (T-DLL), aside from the fact that the despreading signals in T-DLL are replaced by a linear combination of all the users' code sequences with various weightings and timing offsets. The basic principles of MD-DLL are given as follows: 1) to use the decorrelating technique of a multiuser detector to remove the multiple-access interference at the on-time code position instant and 2) to choose a proper timing offset for the code sequences to reduce the weighting imbalance between the two arms of the tracking loop and suppress noise enhancement. The proposed MD-DLL scheme solves the tracking bias problems in a decorrelated delay lock loop under a low-signal-to-noise-ratio (SNR) condition. Computer simulations based on Gold code sequences are used to verify the findings. It is shown that MD-DLL achieves a better and stable S-curve with negligible tracking bias, better rms tracking error and mean-time-to-lose-lock performance under high-SNR conditions, and stronger near-far resistance than T-DLL. [ABSTRACT FROM AUTHOR]

In this paper, five novel schemes based on greedy algorithm are proposed to reduce the peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. For each proposed scheme, a simple transformation is performed on the partial transmit sequences in an iterative fashion to lower the PAPR. Computer simulations results show that all the proposed schemes can achieve PAPR reductions, but the performances of the PAPR reduction are different. To further evaluate their PAPR reductions, we compare the proposed schemes with the iterative flipping scheme. The results show that when the number of subblocks is not large, some of the proposed schemes can offer better PAPR reduction performance than the iterative flipping scheme with comparable computational complexity. [ABSTRACT FROM AUTHOR]

This paper introduces a real-time reliability prediction method for a dynamic system which suffers from a hidden degradation process. The hidden degradation process is firstly identified by use of particle filtering based on measurable outputs of the considered dynamic system. Then the system's reliability. is predicted according to the model of the degradation path. We analyze the identification algorithm mathematically, and validate the effectiveness of this method through computer simulations of a three-vessel water tank. This real-time reliability prediction method is beneficial to the dynamic system's condition monitoring, and may be further helpful to make a proper predictive maintenance policy for the system. [ABSTRACT FROM AUTHOR]

As a loudspeaker's physical size decreases, its ability to reproduce low frequencies is hindered. In this paper we propose a method of creating virtual bass using an efficient frequency tracking algorithm. The proposed algorithm has low computational complexity but excellent performance. The results of computer simulations and subjective tests are presented to validate the algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we suggest a synchronization receiver for MIMO-OFDM based mobile broadcasting system. A MIMO-OFDM receiver with algorithms for tracking of residual frequency offset (RFO) and sampling frequency offset (SFO) is designed and simulated. The proposed synchronization and compensation schemes are applied to IEEE 802.16e WiMAX and its performance is investigated by computer simulations in terms of mean square error (MSE) and bit error rate (BER). The proposed RFO and SFO estimator has a fast convergence and a small residual degradation even for high speed mobile station. [ABSTRACT FROM AUTHOR]

This paper proposes a novel and simple adaptive control algorithm for the effective delay control and resource utilization of end host multicast (EMcast) when the traffic load becomes heavy in a multigroup network with real-time flows constrained by (σ, ρ) regulators. The control algorithm is implemented at the overlay networks and provides more regulations through a novel (σ, ρ, λ) regulator at each group end host who suffers from heavy input traffic. To our knowledge, it is the first work to incorporate traffic regulators into the end host multicast to control heavy traffic output. Our further contributions include a theoretical analysis and a set of results. We prove the existence and calculate the value of the rate threshold ρ* such that for a given set of K groups, when the average rate of traffic entering the group end hosts ρ¯ > ρ*, the ratio of the worst-case multicast delay bound of the proposed (σ, ρ, λ) regulator over the traditional (σ, ρ) regulator is O((Multiple line equation(s) cannot be represented in ASCII text)) for any integer n. We also prove the efficiency of the novel algorithm and regulator in decreasing worst-case delays by conducting computer simulations. [ABSTRACT FROM AUTHOR]

Mobile positioning has drawn significant attention in recent years. Nonline-of-sight (NLOS) propagation error is the dominant error source in mobile positioning. Most previous research in this area has focused on NLOS identification and mitigation. In this paper, we investigate new positioning algorithms to take advantage of the NLOS propagation paths rather than canceling them. Based on a prior information about the NLOS path, a geometrical approach is proposed to estimate mobile location by using two NLOS paths. On top of this, the least-squares (LS)-based position estimation algorithm is developed to take multiple NLOS paths into account, and its performance in terms of root mean-square error (RMSE) is analyzed. A general LS algorithm considering both LOS and NLOS paths is also derived, and the maximum likelihood-based algorithm is presented to jointly estimate the mobile's and scatterers' positions. The Cramer-Rao lower bound on the RMSE is derived for the benchmark of the performance comparison. The performance of the proposed algorithms is evaluated analytically and is done via computer simulations. Numerical results demonstrate that the derived analytical results closely match the simulated results. [ABSTRACT FROM AUTHOR]

This paper deals with the blind separation of instantaneous mixtures of source signals using time-frequency distributions (TFDs). We propose iterative algorithms to perform the nonorthogonal zero diagonalization and/or joint diagonalization of given sets of matrices. As an application, we show that the source separation can be realized by applying one of these algorithms to a set of spatial quadratic TFD matrices corresponding only to the so-called cross-source terms and/or to the so-called autosource terms. The determination of the above matrices to be jointly decomposed requires first an automatic selection procedure of useful time-frequency points. Regarding this last point, we also propose a new selection procedure and a modification of an existing one and provide a comparison with other existing ones. The nonorthogonal joint diagonalization and/or zero diagonalization algorithm's main advantage is to not require (in the blind source separation context) a prewhitening stage, which allows them to work even with a class of correlated signals and provides generally improved separation performance. Finally, an analytical example and computer simulations are provided in order to illustrate the effectiveness of the proposed approach and to compare it with classical ones. [ABSTRACT FROM AUTHOR]

It has been well recognized that significant throughput gains can be leveraged in multiuser wireless communication systems by exploiting multiuser diversity with a smart scheduler. This scheduler collects channel state information (CSI) from all users and allocates the resources to the user(s) experiencing favorable channel conditions. However, for a frequency-division-duplex system with a large number of users, how to efficiently collect the required CSI will be a challenging task, especially when the feedback links are of limited capacity. In this paper, we propose a scheduling algorithm to exploit multiuser diversity with possibly imperfect one-bit channel state feedback. The basic idea is to define a threshold λ and let each user report one-bit information to the scheduler about the comparison between its measured channel fading level and λ. Correspondingly, the scheduler uses these feedback bits to classify all users into two sets and assigns the channel to one user belonging to the set experiencing favorable channel conditions. Several implementation schemes are developed by attacking the optimization of λ under different system configurations, covering both the case when the one-bit feedback is perfect and those when the one-bit feedback is imperfect. Computer simulations show that when the user number is large, say, more than ten users, the proposed scheduling supports significantly larger data rate over the round-robin scheduling, while in comparison with the optimum scheduling with complete CSI, the performance loss is limited if the one-bit feedback is of high reliability. In addition, our studies show that we can effectively enhance the robustness against feedback imperfectness by incorporating the feedback reliability into optimization of λ. [ABSTRACT FROM AUTHOR]

This paper examines three algorithmic approaches for the frequency-domain harmonic-balance method in a coupled device and circuit simulator. These are the nonquasi-static, quasi-static, and modified Volterra series approaches. A detailed qualitative and quantitative comparison between these approaches is provided in terms of accuracy and the computational resources required. [ABSTRACT FROM AUTHOR]

The aim of this paper is to develop efficient online adaptive algorithms for the generalized eigen-decomposition problem which arises in a variety of modern signal processing applications. First, we reinterpret the generalized eigen-decomposition problem as an unconstrained minimization problem by constructing a novel cost function. Second, by applying projection approximation method and recursive least-square (RLS) technique to the cost function, a parallel adaptive algorithm for a basis for the r-dimensional (r > 0) dominant generalized. eigen-subspace and a sequential algorithm based on deflation technique for the first v-dominant generalized eigenvectors are derived. These algorithms can be viewed as counterparts of the extended projection approximation subspace tracking (PAST) and PASTd algorithms, respectively. Furthermore, we modify the parallel algorithm to explicitly estimate the first v-generalized eigenvectors in parallel, not the generalized eigen-subspace. More important, the modified parallel algorithm can be used to extract multiple generalized eigenvectors of two nonstationary sequences, while the proposed sequential algorithm lacks this ability because of slow convergence of minor generalized eigenvectors due to error propagation of the deflation technique. Third, following convergence analysis methods for PAST and PASTd, we prove the asymptotic convergence properties of the proposed algorithms. Finally, computer simulations are performed to investigate the accuracy and the speed advantages of the proposed algorithms. [ABSTRACT FROM AUTHOR]

This paper investigates quantization methods for feeding back the channel information through a low-rate feedback channel in the context of multiple-input single-output (MISO) systems. We propose a new quantizer design criterion for capacity maximization and develop the corresponding iterative vector quantization (VQ) design algorithm. The criterion is based on maximizing the mean-squared weighted inner product (MSwIP) between the optimum and the quantized beamforming vector. The performance of systems with quantized beamforming is analyzed for the independent fading case. This requires finding the density of the squared inner product between the optimum and the quantized beamforming vector, which is obtained by considering a simple approximation of the quantization cell. The approximate density function is used to lower-bound the capacity loss due to quantization, the outage probability, and the bit error probability. The resulting expressions provide insight into the dependence of the performance of transmit beamforming MISO systems on the number of transmit antennas and feedback rate. Computer simulations support the analytical results and indicate that the lower bounds are quite tight. [ABSTRACT FROM AUTHOR]

Recently, ultra wide-band (UWB) wireless communication technology, which provides high data transmission rates and is capable of linearly trading off between throughput and signal-to-noise ratio (SNR), has drawn much attention for short-range wireless networks. To fully exploit its desirable features and to minimize its interference with coexisting other systems requires knowledge of the SNRs at the receivers. In this paper, we propose an algorithm for estimating the pulse energy-to-noise ratio of an UWB signal through utilization of output samples from a correlator in the receiver and evaluate the performance of the proposed algorithm through computer simulation. A notable feature of the proposed algorithm is that it does not affect the effective throughput because the estimation process does not require any additional specific training signals. [ABSTRACT FROM AUTHOR]

This paper examines the performance of the adaptive array antennas used in digital handset systems by studying the minimum mean square error (MMSE) algorithm at 2 GHz. The array is comprised of multiple quarter-wavelength monopole antennas and planar inverted-F antennas (PIFAs). By calculating the spatial correlation between two different directions, we describe how significant enhancement in the capability of reducing interference signals can be achieved, even when the handset is being held in the vicinity of a human operator in the talking position. Secondly, a computer simulation has been carried out under a flat Rayleigh fading environment with multiple cochannel interference signals, in which the average bit error rate (BER) of the handset adaptive array antenna has been characterized for the coherent detection of phase-shift keyed (PSK) signals. The performance of the handset adaptive array is compared to that of an adaptive array comprising plural parallel half-wavelength dipole antennas that are one half-wavelength apart. The performance was also evaluated with regard to the distance between the handset and the human head for different unequal median values and fading correlations of the received signals. The study has revealed that the adaptive array under consideration has substantial potential, not only to reduce the relative power of interference signals, but also to combat multipath fading of the desired signal by using the spatial diversity function of the MMSE, even in close proximity to a human operator. [ABSTRACT FROM AUTHOR]

A new adaptive critic autopilot design for bank-to. turn missiles is presented. In this paper, the architecture of adaptive critic learning scheme contains a fuzzy-basis-function-network based associative search element (ASE), which is employed to approximate nonlinear and complex functions of bank-to-turn missiles, and an adaptive critic element (ACE) generating the reinforcement signal to tune the associative search element. In the design of the adaptive critic autopilot, the control law receives signals from a fixed gain controller, an ASE and an adaptive robust element, which can eliminate approximation errors and disturbances. Traditional adaptive critic reinforcement learning is the problem faced by an agent that must learn behavior through trial-and-error interactions with a dynamic environment, however, the proposed tuning algorithm can significantly shorten the learning time by on-line tuning all parameters of fuzzy basis functions and weights of ASE and ACE. Moreover, the weight updating law derived from the Lyapunov stability theory is capable of guaranteeing both tracking performance and stability. Computer simulation results confirm the effectiveness of the proposed adaptive critic autopilot. [ABSTRACT FROM AUTHOR]

This paper introduces a novel blind equalization algorithm for frequency-selective channels based on a Bayesian formulation of the problem and the sequential importance sampling (SIS) technique. SIS methods rely on building a Monte Carlo (MC) representation of the probability distribution of interest that consists of a set of samples (usually called particles) and associated weights computed recursively in time. We elaborate on this principle to derive blind sequential algorithms that perform maximum a posteriori (MAP) symbol detection without explicit estimation of the channel parameters. In particular, we start with a basic algorithm that only requires the a priori knowledge of the model order of the channel, but we subsequently relax this assumption and investigate novel procedures to handle model order uncertainty as well. The bit error rate (BER) performance of the proposed Bayesian equalizers is evaluated and compared with that of other equalizers through computer simulations. [ABSTRACT FROM AUTHOR]

Independent component analysis is to extract independent signals from their linear mixtures without assuming prior knowledge of their mixing coefficients. As we know, a number of factors are likely to affect separation results in practical applications, such as the number of active sources, the distribution of source signals, and noise. The purpose of this paper to develop a general framework of blind separation from a practical point of view with special emphasis on the activation function adaptation. First, we propose the exponential generative model for probability density functions. A method of constructing an exponential generative model from the activation functions is discussed. Then, a Learning algorithm is derived to update the parameters in the exponential generative model. The learning algorithm for the activation function adaptation is consistent with the one for training the denting model. Stability analysis of the learning algorithm for the activation function is also discussed. Both theoretical analysis and simulations show that the proposed approach is universally convergent regardless of the distributions of sources. Finally, computer simulations are given to demonstrate the effectiveness and validity of the approach. [ABSTRACT FROM AUTHOR]

Conventional fault simulation techniques for field programmable gate arrays (FPGAs) are very complicated and time consuming. The alternative, FPGA fault emulation technique, is incomplete and can be used only after the FPGA chip is manufactured. In this paper, we present efficient algorithms for computing the fault coverage of a given FPGA test configuration. The faults considered are opens and shorts in FPGA interconnects. The presented technique is able to report all detectable and undetectable faults and, compared with conventional methods, is orders of magnitude faster. [ABSTRACT FROM AUTHOR]

The identification of model parameters of a highs density recording channel is usually difficult and complicated. In this paper, we successfully apply the alternating coordinates minimization (ACM) algorithm for estimating parameters of a partial erasure plus transition shift model (PETSM). The resulting algorithm turns out to iteratively solve two least square problems and is guaranteed to converge. Furthermore, the obtained model for a nonlinear partial response channel is more accurate than conventional models such that the maximum likelihood (ML) detector has better bit error rate (BER) performance without increasing its realization complexity. Computer simulations show that the ACM algorithm can accurately estimate the model parameters and the BER for the detector is significantly improved especially when the transition shift parameter is large. [ABSTRACT FROM AUTHOR]