In the presence of nonlinearity, we analyze the impact of the selected mapping (SLM) technique on bit-error-rate (BER) performance of orthogonal frequency division multiplexing (OFDM) systems in an additive white Gaussian noise channel. The peak-to-average-ratio (PAR) reduction gain of SLM can be increased by improving the PAR statistics at the cost of complexity in the OFDM transmitter, thereby helping to decrease the required power amplifier (PA) output backoff (OBO). However, since the PAR statistics focus only on the statistical distribution of the highest peak in an OFDM symbol, the statistics cannot be used to quantify BER performance degradation in the presence of nonlinearity such as that caused by a PA or digital-to-analog converter (DAC). We first derive a closed-form expression for the envelope power distribution in an OFDM system with SLM. Then, using this derived envelope power distribution, we investigate the BER performance and the total degradation (TD) of OFDM systems with SLM under the existence of nonlinearity. We discuss peak backoff (PBO) and the clipping ratio, which determine the operating point of the PA and dynamic range of the DAC, respectively. Lastly, we consider the total degradation (TD), which indicates the tradeoff between the OBO and the E_b/N_o penalty due to nonlinearity, and numerically compute the PBO and clipping ratio that minimize the TD. The TD-minimizing PBO and clipping ratio are given as functions of the number of candidate signals in SLM.

The active constellation extension (ACE) technique is attractive for reducing peak power in OFDM systems. It is simple and easy to implement and provides suboptimal gain in peak power reduction. However, its peak power reduction capacity is sensitive to low target clipping ratios. In this paper, we propose a novel ACE algorithm using pilot symbols. In contrast to the existing ACE techniques, our proposed algorithm can reach any desired target clipping level with low complexity, even when the clipping level is set below the initially unknown optimum value. Simulation results are utilized to compare our proposed algorithm with the existing ACE techniques. It is shown that our proposed algorithm provides better peak-to-average power ratio (PAR) reduction performance for low clipping ratios.

In Orthogonal Frequency Division Multiplexing, a simple clipping method is widely used in order to reduce the peak-to-average power ratio since it is easy to implement. The performance analysis of the clipping approach has been previously introduced in the literature. Clipping, however, is a nonlinear process and may cause two major undesirable effects: (i) spectral regrowth, which causes unacceptable out-of-band radiation; and (ii) distortion of the desired signal, which increases bit-error-rate (BER). The out-of-band radiation can and often is suppressed by filtering, which leads to peak regrowth. Therefore, iterative clipping and filtering is required until the desired clipping level is achieved. However, this iterative process makes BER estimation difficult. This letter provides expressions and analytical techniques for estimating the attenuation factor, error vector magnitude, and BER, using a noise enhancement factor that is obtained by simulation. Simulation results show strong agreement with our semi-analytical results for 1024 subcarriers.

Space-time block codes (STBCs) from coordinate interleaved orthogonal designs (CIODs) offer several advantages including full-diversity and single-symbol decodability. In an effort to assess their performance in quasi-static frequency nonselective i.i.d. Nakagami-m fading channels, we analyze the error rate, outage capacity, and information outage probability. First, based on an accurate closed-form formula for the average symbol pairwise error rate (SPER), we derive tight union upper and lower bounds on the symbol-error rate (SER). Second, we apply Gaussian and Gamma approximations to provide closed form expressions for the outage capacity. Third, using high signal-to-noise ratio (SNR) and moment-matching approximation techniques, we also derive accurate closed-form approximations for the information outage probability (IOP). Finally, we show that STBCs from CIODs provide full-diversity by deriving SER based and IOP-based asymptotic and instantaneous diversity orders. Monte-Carlo simulations show that the analytical results agree with simulation experiments.

Selected mapping (SLM) techniques have been used to reduce the high peak-to-average power ratio (PAR) in Orthogonal Frequency Division Multiplexing (OFDM) systems. The capacity of PAR reduction can be increased by improving the PAR statistics at the cost of complexity of the OFDM transmitter. However, it is difficult to clarify the performance degradation in the presence of nonlinearities, such as a power amplifier (PA), with the PAR metric because the statistical distribution of PAR focuses only on the highest peak, even though PAR reduction can help to reduce the required PA backoff. The nonlinear distortion is related to the amount of signal greater than the saturated threshold value; therefore, it is desirable to know the envelope power distribution. In this paper, we derive a closed form expression for the envelope power distribution in SLM/OFDM systems with nonlinearity, and verify the derived expression with simulation results.

Space-time block codes (STBCs) from coordinate interleaved orthogonal designs (CIODs) have attracted considerable attention lately due to their full-diversity and single-symbol decodability for multiple antenna systems. In this letter, we analyze the information outage probability of STBCs from symmetric structured CIODs in quasi-static frequency-nonselective Rayleigh fading channels. By using the probability density function (PDF) and the cumulative distribution function (CDF) of the product of two i.i.d. chi-square random variables and then exploiting a moment-matching approximation technique, we derive an accurate closed-form approximation for the information outage probability of symmetric CIODs and a corresponding asymptotic diversity order, the results of which can be used to theoretically predict the performance of symmetric CIODs with various antenna configurations in non-ergodic Rayleigh fading channels. Some simulations are performed to verify the accuracy of the derived formulas and illustrate the theoretical results.

We find that placing each pilot tone in an equally spaced manner according to the conventional placement scheme is not suitable for doubly selective channel estimation. In this paper, we propose an efficient pilot tone placement scheme enabling accurate channel estimation in OFDM systems regardless of time variations of a channel. Since the number of channel impulse response taps to be estimated is typically much greater than the number of pilot tones, linear minimum mean square error (LMMSE) estimation schemes for time-invariant channels cannot be straightforwardly extended to doubly selective channel estimation. To overcome this problem, we propose an accurate LMMSE channel estimator that exploits a small number of pilot tones located according to the derived pilot placement. To achieve performance close to the LMMSE estimator but with lower complexity, an approximate LMMSE (ALMMSE) channel estimator is also proposed. Finally, we propose a novel iterative ALMMSE channel estimator that achieves better performance than the LMMSE and ALMMSE estimators, while having complexity in between the two.

By providing both spatial diversity and multiplexing gains simultaneously, double space-time transmit diversity (D-STTD) is considered a promising technique for future multiple antenna wireless systems. Although originally proposed D-STTD is an open-loop scheme, transmit antenna grouping (also called antenna shuffling) with low-rate feedback information from the receiver can significantly improve the performance of open-loop D-STTD even in spatially correlated Rayleigh fading channels, since the antenna grouping method selects the best antenna grouping pattern corresponding to the channel realization. In this paper we propose a new antenna grouping method based on the criterion of maximum mutual information. Showing the same performance improvement as the existing antenna grouping method based on the criterion of maximum post-processing signal-to-noise ratio (SNR), the proposed low-complexity mutual information-based antenna grouping method can be performed with less complexity. We verify the effectiveness of our proposed method by numerical simulations even for a spatial correlation channel model based on practical channel measurements.

Abstract — Internet paths sharing the same bottleneck can be identified using several shared congestion detection techniques. However, all of these techniques have been designed to detect shared congestion between a pair of paths. To cluster N paths by shared congestion, a straightforward approach of using pairwise tests would require O(N 2) time complexity. In this paper, we present a scalable approach to cluster Internet paths based on DCW (Delay Correlation with Wavelet denoising) which does not require a common end point between paths. We present a function to map each path’s measurement data into a point in a multidimensional space such that points are close to each other if and only if the corresponding paths share congestion. Because points in the space are indexed using a tree-like structure, the computational complexity of clustering N paths can be reduced to O(N log N). The indexing overhead can be further improved by reducing dimensionality of the space through wavelet transform. Computation cost is kept low by reusing for dimensionality reduction the same wavelet coefficients obtained in DCW. Our approach is evaluated by simulations and found to be effective for a large N. The tradeoff between dimensionality and clustering accuracy is shown empirically. I.

Double space-time transmit diversity (D-STTD) is considered a promising technique for future multiple antenna wireless systems, since it provides both spatial diversity and multiplexing gains simultaneously. To further improve the performance of D-STTD, we propose a novel adaptive transmission technique. Although the originally proposed D-STTD is an open-loop scheme, the proposed adaptive scheme utilizes low-rate feedback information, which can significantly improve the performance of the open-loop D-STTD. Furthermore, when the adaptive scheme is jointly combined with the antenna shuffling scheme, it outperforms the existing antenna shuffling schemes with the same feedback information.

In this paper, we propose QR-decomposition-based unordered/ordered decorrelating decision-feedback detection (D-DFD) schemes with linear or D-DFD symbol estimators for a double space-time transmit diversity (D-STTD) system. The time-selective fading mobile channel severely degrades the performance of conventional detectors, since the time-selectivity of the fading channel destroys the orthogonality of the space-time codeword. Moreover, the complexity of the known symbol-by-symbol detectors is too high to be implemented, due to the multiple channel inversions. In contrast, through the block-by-block QR-decomposition, our proposed methods can decorrelate the two STTD units while preserving the Alamouti-like codeword structure and exploit this structure to efficiently estimate the symbols corrupted by the severe time-selective fading channels.

In orthogonal frequency division multiplexing (OFDM) systems, time-frequency-selective, equivalently time-variant multipath fading destroys subcarrier orthogonality, resulting in intercarrier interference (ICI). OFDM systems with guard interval (GI) can prevent intersymbol interference (ISI) caused by frequency-selective fading, but do not combat ICI caused by time-selective fading. To mitigate the effects of ICI, several estimation methods have been proposed. These conventional algorithms are highly complex in general due to the large-sized matrix inversion. In this paper, we propose an efficient OFDM symbol estimation scheme, called iterative sequential neighbor search (ISNS) algorithm, which achieves an enhanced performance with a moderate complexity compared with the conventional methods. The validity of the proposed estimation scheme is demonstrated by computer simulations.

In conventional discrete multitone (DMT) systems, a multitap time-domain equalizer (TEQ) is used to shorten the channel length, so that the bandwidth efficiency reduction due to cyclic extension is relieved. The TEQ, however, tends to introduce spectral nulls which degrade the achievable signal-to-noise ratio at corresponding subchannels, thereby decreasing the bandwidth efficiency. Furthermore, computationally expensive joint TEQ initialization and optimal delay (introduced by TEQ) selection is necessary. In this paper, a novel subsymbol-equalization scheme is proposed, and is based on the observation that the high-bit-rate twisted-pair channels rarely contain a zero that is close to the unit circle. Although a delay of a fraction of a DMT symbol period is introduced, the proposed subsymbol-equalization scheme eliminates the necessity of both the channel shortening at the receiver and the cyclic extension at the transmitter. Simulation results demonstrate the computational efficiency (no TEQ) and the bandwidth efficiency of the proposed subsymbol-equalization scheme.

In this paper, receiver designs for orthogonal frequency-division multiplexing (OFDM) systems that exploit the Alamouti transmit diversity technique are addressed. In Alamouti space-time coded OFDM systems, the simple Alamouti decoding at the receiver relies on the assumption that the channels do not change over an Alamouti codeword period (two consecutive OFDM symbol periods). Unfortunately, when the channel is fast fading, the assumption is not met, resulting in severe performance degradation. In this paper, a sequential decision feedback sequence estimation (SDFSE) scheme with an adaptive threshold (AT), a traditionally single-carrier equalization technique, is used to mitigate the performance degradation. A new method to set the threshold value is proposed. For small signal constellations like BPSK and QPSK, the SDFSE with an AT requires much lower complexity than a previous minimum mean square error approach at the cost of a small performance degradation. Furthermore, we show that the performance difference becomes smaller when channel estimation error is included. An adaptive effort sequence estimation (AESE) scheme is also proposed to furthur reduce the average complexity of the SDFSE scheme with an AT. The AESE scheme is based on the observation that a high Doppler frequency does not necessarily mean significant instantaneous channel variation. Simulations show the efficacy of the proposed SDFSE with an AT and the AESE.

We propose a new switched transmit diversity technique in MIMO systems with an application to Alamouti's space time block coding. The proposed scheme is basically a closed loop system where the feedback bits are sent back to the transmitter to indicate the channel quality. Various switching strategies, depending on the size of feedback bits, are considered and optimized to compare the trade-off between the link performance and the number of antennas or feedback information. From our analytical and numerical results, we show that there is a considerable benefit in terms of the performance and practical use.

The high power amplifier (HPA) is a key part of the transmit chain, but inherently nonlinear. Nonlinearity of the HPA causes intermodulation distortion (IMD). In order to compensate for the IMD, linearization techniques are required. Digital predistortion is one such technique. In this paper, we present an overview of the digital predistortion linearizer that we developed and the experimental results of applying this linearizer to an HPA for IS-95. The experimental results show that the developed linearizer effectively suppresses the IMD by 7 to 10 dB depending on the signal bandwidth.

Multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems are attractive because of their large capacity and high data rate. The paper presents a blind channel estimation method for MIMO-OFDM systems with and without a cyclic prefix (CP) by using the presence of virtual carriers. The proposed method is based on the noise subspace method. In addition, we establish a sufficient condition for channels to be identifiable. The proposed algorithm can be applied to MIMO-OFDM systems with insufficient CP or no CP, thereby potentially increasing channel utilization. Furthermore, by using reduced CP or no CP, the proposed method can achieve lower computational complexity. We present simulation results demonstrating the performance of the proposed method via numerical experiments.

The overlay network approach is an emerging technique to satisfy the strict requirements for various real-time multimedia services. However, overlay networks suffer from a shared congestion problem since each unicast flow may interfere with each other in the common underlying links. Most previous techniques to detect shared congestion have limitations when applied as a general solution, since they assume perfect synchronization between probing packets. However, our recent work shows that a technique based on wavelet denoising can overcome the limitations by mitigating the interfering effects such as synchronization offset and the random fluctuations of queueing delay; the proposed technique provides a more robust and accurate detection in the presence of a large amount of synchronization offset In this paper, wavelet denoising is tailored to the characteristics of queueing delay on packet networks. The wavelet denoising based technique is verified through extensive simulations. The efficacy of the proposed approach is demonstrated by the detection accuracy and convergence speed.

Per-flow congestion control helps endpoints fairly and efficiently share network resources. Better utilization of network resources can be achieved, however, if congestion management algorithms can determine when two different flows share a congested link. Such knowledge can be used to implement cooperative congestion control or improve the overlay topology of a P2P system. Previous techniques to detect shared congestion either assume a common source or destination node, drop-tail queueing, or a single point of congestion. We propose in this paper a novel technique, applicable to any pair of paths on the Internet, without such limitations. Our technique employs a signal processing method, wavelet denoising, to separate queueing delay caused by network congestion from various other delay variations. Our wavelet-based technique is evaluated through both simulations and Internet experiments. We show that, when detecting shared congestion of paths with a common endpoint, our technique provides faster convergence and higher accuracy while using fewer packets than previous techniques, and that it also accurately determines when there is no shared congestion. Furthermore, we show that our technique is robust and accurate for paths without a common endpoint or synchronized clocks; more specifically, it can tolerate a synchronization offset of up to one second between two packet flows.

In this paper, we investigate diversity combining schemes for OFDM wireless LAN systems with antenna array. Current standards were designed for diversity selection instead of combining. It is well known that the combining results in a higher receiver gain than the selection. However, the combining requires significantly more complexity than the selection. This paper is focused on implementing a low-complexity diversity combining scheme, which reduces the complexity in vector channel estimation. We demonstrate the performance of the proposed combining scheme via computer simulations.

In this paper, a new bandwidth efficient OFDM transmission scheme is proposed. A bandwidth efficient iterative scheme for OFDM systems without using cyclic prefix was proposed before [3] which works well when a channel does not have a deep spectral null. But such a frequency domain deep null is common in a wireless channel. A bandwidth efficient scheme proposed in this paper works well regardless of the existence of spectral null. In the proposed scheme, OFDM symbols are recovered in two steps. In the first step, only a small portion of the time domain OFDM symbol is recovered by the frequency domain 1-tap equalizer. In the second step, the recovered small portion and the tail part of the previous symbol are used for the cyclic reconstruction and tail cancellation. Simulation experiments are conducted to validate the proposed scheme.

This paper presents a new simplified predistortion scheme to compensate nonlinear distortion introduced by the high power amplifier (HPA) in OFDM systems. OFDM systems are susceptible to HPA nonlinearities in particular because of their large peak-to-average power ratios. Previously, a Volterra-based predistorter was suggested for compensation of HPA's nonlinear distortion in OFDM systems. In contrast to this earlier work, our adaptive predistorter utilizes a more simplified structure. It is shown that the new simplified structure exhibits faster convergence than the previous Volterra-based predistorter. In addition, the performance of the new predistortion scheme for OFDM systems is evaluated in terms of total degradation, optimal output backoff, and BER. Simulation results also show that our predistortion scheme is more efficient in compensating the nonlinear distortion of HPAs in OFDM systems than the previous scheme.

The statistical properties for bicoherence estimation are shown to be strongly connected to the properties of the power- and bispectral estimator used. Data tapering will reduce spectral leakage and frequency smoothing will reduce the variance. It is shown that correct normalization is essential to ensure unbiased results. The multitaper approach is shown to be superior to other non-parametric estimators for bicoherence estimation.

Transmit diversity and space-time coding have received a lot of attention in previous years. We propose a direction-time transmit scheme for a fast block fading channel which exploits the parametric structure of the time-varying vector channel. Specular propagation and local scattering are assumed at the base-station and mobile station respectively. The partial channel knowledge needed for the transmit design includes: the number of specular paths, path direction vectors and length of the coherent interval. Transmission matrix codewords are formed according to this partial channel information such that multiple channels are induced and symbols are spread over different transmission directions. Diversity gain and blind channel estimation are achieved simultaneously at the mobile station through equalization.

A practical and effective approach is proposed to detect a transient or non-stationary signal component of interest from a composite signal waveform. The detection problem has been re-formulated in terms of time-frequency analysis, and, thus, the conventional 1D (ie, time-domain) matched filter approach is extended to the 2D (here, time-frequency domain) optimal filtering. For that purpose, the reduced interference distribution (RID) algorithm, the outer product expansion of the time-frequency distribution, the singular value decomposition (SVD), and a priori available time-frequency information of a signal part of interest are employed to derive a time-frequency domain matched filter by utilizing the singular values of the sampled time-frequency distribution and the corresponding fractions of signal energy. Finally, one real problem of detecting the snare drum sound event from a measured musical signal is considered to demonstrate the performance of the proposed approach.

This paper presents an adaptive predistorter to compensate nonlinear distortion introduced by the high power amplifier (HPA) in OFDM systems. OFDM systems are susceptible to HPA nonlinearities in particular because of their large peak-to-average power ratios. In contrast to earlier work, the adaptive predistorter in this paper is based on both the direct and indirect learning architectures, and utilizes a complex Volterra series which is known to be suitable for compensating nonlinear phenomena. It is shown that the new predistorter scheme exhibits faster convergence than the previous method based on the indirect learning architecture only. In addition, the performance of the predistorter for OFDM systems is evaluated in terms of total degradation, optimal output backoff, and BER.

We utilize wavelet-based hidden Markov models (HMM) to classify electric power transient disturbances associated with degradation of power quality. Since the wavelet transform extracts power transient disturbance characteristics very well, this wavelet-based HMM classifier illustrates high classification correctness rates. The power transient disturbance is decomposed into multi-resolution wavelet domains, and the wavelet coefficients are modeled by a HMM. Based on this modeling, the maximum likelihood classification is applied to classify actual power quality transient disturbance data recorded on a 7200 V distribution line, and the result is tuned by post-processing. Of 507 power quality events experimentally observed by an electrical utility, 95.5% are correctly classified.

Orthogonal frequency division multiplexing (OFDM) is a method suitable for high-rate data transmission in wireline and wireless communications. However, it is very sensitive to frequency offset due to Doppler shifts and carrier synchronization errors. This frequency offset results in inter-carrier interference (ICI) and, as a result, the performance of the OFDM system degrades drastically. Consequently, it, is necessary to remove as many ICI effects as possible to achieve the desired OFDM system performance. Therefore, in this paper, we propose a new method based on a nonlinear adaptive filter to suppress these ICI effects. In addition to showing that the ICI effects can be reduced significantly, the results also demonstrate that the nonlinear filter scheme is superior to the conventional linear filter.

This paper presents a new power-line disturbance detection algorithm. The utilized recursive least square (RLS) prediction error filter extracts the power-line disturbance signal from recorded data, and the modified stop-and-go cell average constant false alarm rate (CA CFAR) detector makes a decision based on the squared output of the previous stage. The detection performance of the proposed algorithm is determined by simulations, and actual high voltage transmission line data is utilized to demonstrate the performance of the proposed algorithm.

This paper presents a new predistorter design technique for combating the nonlinear distortion of orthogonal frequency division multiplexing (OFDM) signals in the presence of a nonlinear high power amplifier (HPA). The performance of the predistorted OFDM system is demonstrated via bit error rate, output power back off and total degradation. It is shown that the performance of the OFDM system linearized by the proposed predistorter is significantly better than that without the predistorter, and the performance approaches that of the OFDM system linearized by an ideal predistorter.

This paper presents the performance evaluation of a fast third-order Volterra digital filtering algorithm mapped onto an AT&T DSP-3 parallel processor. Five different implementations are considered. Speed-up results indicate that the "time-skewing" method is currently the fastest. An application to nonlinear communication channel equalization using a 64-QAM signal constellation is presented.

The objective of this paper is to present an adaptive algorithm to identify third-order frequency-domain Volterra filter coefficients, which correspond to the discrete Fourier transform (DFT) of the time-domain Volterra filter coefficients. The approach rests upon the block least mean square (LMS) algorithm based on the overlap-save method.

A practical and efficient method is presented for the counting of third-order products generated by an arbitrary number of carriers with arbitrary power spectral shapes. In particular, three selective counting procedures (i.e. sorting by position, sorting by position and group, and sorting by position, group, and kind) are introduced in a systemic way, based upon a discrete third-order Volterra model. The advantage of the counting algorithm is that (1) the algorithm provides the exact counting of third-order products of all eleven possible groups; (2) the counting process requires only two multiplications for the selective counting of third-order products at each position, and the algorithm, which is thus efficient, can be easily implemented.>

The objective of this paper is to indicate how digital higher-order spectral analysis may be used to determine linear and cubic radar cross sections given time series data representing the transmitted and received signals. The approach utilizes an orthogonal Volterra-like model. In this case, the absolute value squared of the linear and cubic frequency-domain "orthogonal" kernels can be directly related to the linear and cubic radar cross sections, respectively. Of note is the fact that the approach makes no assumptions concerning the statistics of the transmitted signal.>

Two methods (two-tone input approach and random process input approach) for the estimation of harmonic and intermodulation distortion of nonlinear systems are compared. The random input approach, where a nonlinear system is modeled by a second-order Volterra series, is examined in terms of its statistical properties, and its advantages and limitations over the classical two-tone input approach. Experimental results are shown where these two approaches are applied to evaluate second-order distortion of a loudspeaker and to compare the performance of these approaches in terms of Volterra kernels and distortion factors.>

For higher-order Volterra systems with arbitrary stationary inputs, an orthogonalization scheme based upon ordered sets of conditioned orthogonal higher-order input vectors in the frequency domain using Gram-Schmidt method is presented. A new set of nonlinear transfer functions for the conditioned orthogonal Volterra system is obtained from a coordinate transformation of a Volterra system based upon nonorthogonal higher-order input vectors. The orthogonal modes has the same minimum mean square error as the original system but without hybrid coherences, thus allowing physically meaningful interpretation of nonlinearities of systems.>

The properties of higher-order moment sequences and higher-order spectral moments of an independent, identically distributed (i.i.d.) process up to fourth order are discussed. These properties are utilized to develop algorithms to identify time-invariant nonlinear systems, which can be represented by second-order Volterra series and which are subjected to an i.i.d. input, in both the time and frequency domain. A relatively simple solution for estimating the Volterra kernels, which requires neither the calculation of the moment sequences for various time lags (or higher-order spectral moments) of the input nor the calculation of the inverse matrix, is shown to exist, even though the second-order Volterra series is not an orthogonal model for an i.i.d. input (unless the input is a white Gaussian process).>

The authors examine the sources of numerical instabilities in fast RLS (recursive least squares) algorithms as well as the statistical properties of the soft constrained initialization based on a necessary condition x/sub N/(0)=0/sub N/, for the fast RLS algorithms. It is pointed out that x/sub N/(0)=0/sub N/ is essential in order to reduce the computational complexity as well as the error propagation effects. The structural sources of the fast RLS algorithms, which cause the numerical instability, are examined. The soft constrained initialization of the fast RLS algorithm based on X/sub N/(0)=0/sub N/ is analyzed and interpreted.>

A digital spectral method of evaluating second-order distortion of a nonlinear system, which can be represented by Volterra kernels up to second-order and which is subjected to a random noise input, is discussed. A fundamental assumption that the input possesses Gaussian statistics is investigated. Deleterious effects and misleading results of assuming that the input is Gaussian when in fact it is not are demonstrated. The proposed approach is utilized to model, identify, and quantify the linear response and second-order distortion products of a loudspeaker in the low-frequency band by using higher-order coherence spectra.>

A method for estimating time-frequency representations of nonstationary signals using recursive least squares (RLS) with variable forgetting factors is described. The variable forgetting factor is adapted to a nonstationary signal by an extended prediction error criterion which accounts for the nonstationarity of the signal. This method has good adaptability in the nonstationary situation and low variance in the stationary situation.>

A frequency-domain block recursive least-square adaptive algorithm is presented for the identification of nonlinear systems which can be modeled by a third-order Volterra series. The identification algorithm is based on the application of the Volterra theory and adaptive signal-processing techniques. The approach does not assume any particular statistics of the input. Moreover, the adaptive algorithm can be used, with a little modification, for the identification of a second-order Volterra system driven by stationary random inputs.>

Spectral estimation of the nonlinear transfer functions (linear, quadratic, and cubic) of a nonlinear system with stationary nonGaussian inputs, which can be modeled by single-input/single-output third-order Volterra functionals is presented. This method is general in the sense that it does not depend on the input statistics. The practicality and the feasibility of the digital implementation of the method are tested by analyzing simulated input-output data of known cubically nonlinear systems. In addition, the notion of coherency is extended to cubically nonlinear systems and generalized for nonGaussian inputs.>

When analyzing various signals produced by some nonlinear process, higher-order spectra are necessary to characterize the nonlinearity. For example, the bispectrum is very useful in analyzing three-wave nonlinear interaction data. An optimized parametric bispectrum estimation method is presented. It is shown to be particularly advantageous when estimating from either short duration records, or under poor signal-to-noise ratio conditions. The performance is compared to a nonoptimized parametric algorithm as well as the FFT (fast Fourier transform) approach.>

A new digital method of estimating linear and quadratic transfer functions of a quadratic system with a general random input is presented. The feasibility of the technique is demonstrated by analyzing simulated data. It is also shown that considerable error occurs in estimating the transfer functions based on a Gaussian input assumption, when in fact the input is non-Gaussian.

New efficient autocorrelation and lattice methods of MEM spectral estimation are presented. In these methods, the "covariance property" of Gaussian distributions is exploited such that autocorrelation samples or lattice parameters can be computed with addition operations only. Also the performance of the proposed lattice method is studied through simulations and its application to the problem of spectral analysis of the vibrational modes of damaged and undamaged aircraft wings.

A novel approach to nonlinear filtering with minimum mean square error criterion is presented. This method considers the class of nonlinear filters with Volterra series structures under the assumption that filter inputs are Gaussian, and a relatively simple solution results which is directly applicable in many practical situations. Moreover, two simple parameter adaption algorithms for the second order Volterra filter are presented and it is shown that their convergence speeds depend on the squared ratio of maximum to minimum eigenvalues of the input autocovariance matrix. Finally, the lattice orthogonalization of filter input is considered for faster convergence.