Time-domain Estimation Research Articles

Frequency-Domain Carrier Frequency and Symbol Timing Offsets Estimation for Offset QAM Filter Bank Multicarrier Systems in Uplink of Multiple Access Networks

In this paper, we study carrier frequency offset (CFO) and symbol timing offset (STO) estimation in the uplink of multiuser offset QAM filter bank multicarrier (FBMC) communication systems. A low-complexity frequency-domain CFO estimator using periodical training sequence is proposed. Also a good estimate of STO is obtained by maximizing the energy of subcarriers subject to training sequence at the output of analysis filter bank. Furthermore we derive the theoretical MSE for the proposed CFO estimator. Computer simulations show that the derived MSE matches the simulated MSE closely. Compared with state-of-the-art time domain estimator, the proposed estimator achieves better performance with a lower computational complexity.

Alpha Frequency Estimation in Patients With Epilepsy

We report comparison and assessment of the clinical utility of different automated methods for the estimation of the alpha frequency in electroencephalograph (EEG) and compare them with visual evaluation. A total of 56 consecutive patients, aged 17 to 78 years, who had a routine EEG recording, were included, and they were grouped as patients with epilepsy (Ep) and without epilepsy (nEp). Five different methods were used for alpha frequency estimation: visually guided manual counting and visually guided Fourier transform, and 3 methods were fully automated: time domain estimation of alpha (automatic assessment of alpha waves in time domain [ATD]) and 2 fast Fourier transform (FFT)-based methods, a segmented (automatic assessment of EEG segments by FFT) and one full FFT (automatic assessment of whole EEG by one FFT of the full recording [AWF]). The AWF discriminated significantly between Ep and nEp. Visually guided manual counting showed an almost significant difference independently in the 2 occipital electrodes. The ATD underestimated high frequencies and returned a too low mean frequency. This study shows that AWF is the best suited method for automatic assessment of the alpha frequency.

Nonlinear Identification Approach of Nonlinear Constitutive Model of Soil Material with Optimization Procedure

Model identification of dynamic systems in the vibration engineering field has been followed with interest in recent years. A number of identification techniques on this topic are now available, such as parametric or non-parametric identification methods, time domain or frequency domain estimation approaches, etc. The identification approach of nonlinear constitutive model from input-output measurements is proposed. The inverse problem of material characterization is formulated as parameter identification problem that is solved by using optimization procedure. A set of parameters corresponding to the material property can be determined by minimizing objective function which accounts for experimental data and calculated responses of the mechanical model. The performances of the proposed identification approach were evaluated with simulating data. The effectiveness of identification approach is validated by numerical simulation. The investigation results show that the proposed identification algorithm poses good robustness and high identification precision.

Discrete fourier transform-based TOA estimation in UWB systems

In this paper, we propose two time of arrival estimators for ultra wideband signals based on the phase difference between the discrete Fourier transforms (DFT) of the transmitted and received signals. The first estimator is based on the slope of the unwrapped phase and the second one on the absolute unwrapped phase. We derive the statistics of the unwrapped phase. We show that slope-based estimation almost achieves asymptotically the baseband Cramer-Rao lower bound (CRLB), while the absolute-phase-based estimator achieves asymptotically the passband CRLB. We compare the proposed estimators to the time-domain maximum likelihood estimator (MLE). We show that the MLE achieves the CRLB faster than the DFT-based estimator, while the DFT-based estimator outperforms the MLE for low signal to noise ratios. We describe also how to use the proposed estimators in multipath UWB channels.

Advanced Receiver Design for Mitigating Multiple RF Impairments in OFDM Systems: Algorithms and RF Measurements

Direct‐conversion architecture‐based orthogonal frequency division multiplexing (OFDM) systems are troubled by impairments such as in‐phase and quadrature‐phase (I/Q) imbalance and carrier frequency offset (CFO). These impairments are unavoidable in any practical implementation and severely degrade the obtainable link performance. In this contribution, we study the joint impact of frequency‐selective I/Q imbalance at both transmitter and receiver together with channel distortions and CFO error. Two estimation and compensation structures based on different pilot patterns are proposed for coping with such impairments. The first structure is based on preamble pilot pattern while the second one assumes a sparse pilot pattern. The proposed estimation/compensation structures are able to separate the individual impairments, which are then compensated in the reverse order of their appearance at the receiver. We present time‐domain estimation and compensation algorithms for receiver I/Q imbalance and CFO and propose low‐complexity algorithms for the compensation of channel distortions and transmitter IQ imbalance. The performance of the compensation algorithms is investigated with computer simulations as well as with practical radio frequency (RF) measurements. The performance results indicate that the proposed techniques provide close to the ideal performance both in simulations and measurements.

단일 반송파 주파수 영역 등화 시스템을 위한 공통 위상 추적 기법 연구

주파수 영역 등화 기법은 다중 반송파 시스템의 대표적 특정으로 단일 탭의 채널 등화로 인한 낮은 구현 복잡도의 장점을 갖는다. SC-FDE (single carrier frequency domain equalization) 시스템은 단일 반송파 시스템에서 주파수 영역 등화 기법을 채택하고, 지연 확산에 대한 강점을 갖기 위해 CP(cyclic prefix)를 포함한 형태의 구조를 갖는다. 단일 반송파 시스템에서 동기 및 등화기를 거친 후 잔존하는, 공통 위상 오프셋 성분을 제거해야만 한다. 공통 위상 오프셋 성분은 송수신기 간 반송파 주파수 생성 시 발생하는 성분이기 때문에 이 오프셋이 큰 경우 성능 열화의 원인이 된다. 본 논문에서는 SC-FDE 시스템에서 공통 위상 오프셋 성분을 주파수 영역에서 보정하는 기법을 제안하였다. 동기 획득 및 등화를 위한 훈련 신호는 자기 상관관계 특성이 우수한 CAZAC (constant amplitude zero autocorrelation code) 시퀀스를 채택하였다. 제안한 공통 위상 오프셋 추적 성능은 컴퓨터 모의실험을 통해 평균 제곱 오차 (mean square error, MSE) 성능을 통해 확인하였고, 그 성능이 시간 영역에서 보정하는 것과 유사한 MSE 성능을 갖는 것을 확인하였다. Frequency domain equalization is the most promising technology that has relatively low complexity in multipath channel. A frame of single carrier system with frequency domain equalization (SC-FDE) has cyclic prefix to mitigate effect of delay spread. After synchronization and equalization procedure on the SC-FDE system, common phase offset (CPO) that can introduce performance degradation caused by phase mismatch between transmitter and receiver oscillators is remained. In this paper, common phase offset tracking in frequency domain is proposed. To track CPO, constant amplitude zero autocorrelation code sequence as training sequence is adopted. By using numerical results, performance of mean square error is evaluated. The results show that MSE of CPO has similar performance compare to the time-domain estimation and there is no need of domain conversion.

Weak Signal De-noising Based on Accumulated Average in Time-domain and Bi-spectrum estimation

To the wideband weak signal from distributed optical fiber temperature sensing system, the traditional measurement method of the weak signal was not perfect. On the basis of analyzing the time-domain accumulated average algorithm and bi-spectrum estimation algorithm, the method that combine the cumulative average and bi-spectrum estimation was presented which can do-noise the weak signal collected from the sensor. The simulation analysis shows that the method can extract the useful signal effectively and restrain the noise.

A closed-form expanded autocorrelation method for frequency estimation of a sinusoid

A closed-form expanded autocorrelation method for real single-tone frequency estimation is proposed. Firstly, the modified covariance (MC) method based on multiple autocorrelation lags is applied to provide a coarse frequency estimate. Then, a closed-form adjustment term based on a least square cost function is derived to get the fine frequency estimate. Simulation results show that the performance of the proposed algorithm, when compared with several existing closed-form time-domain estimators, is closer to the Cramer–Rao bound (CRB). Moreover, the proposed method has lower computation complexity than other autocorrelation-based approaches, which also use multiple autocorrelation lags.

A Novel Frequency Synchronization Algorithm Based on PN Sequences and Pilots for TFU-OFDM Systems

In this paper, a novel frequency synchronization algorithm for a new modulation scheme named time domain and frequency domain united orthogonal frequency division multiplexing (TFU-OFDM) is introduced. The frequency synchronization method has two-steps, which joints time and frequency domain estimation based on PN sequences and pilots. We utilize the PN sequences as guard intervals in time domain to achieve the first-step estimation and the second-step is realized by the pilots in data blocks in frequency domain. The simulation results and analysis show that the proposed frequency synchronization method could achieve fast and reliable synchronization and sufficient precision, and provides excellent performance for TFU-OFDM systems.

Enhanced sampling clock offset correction based on time domain estimation scheme

This paper is concerned with the issue of sampling clock synchronization and correction. First, we make an analysis of the cause of the sampling clock offset and its effect on the performance of communication systems. A novel time domain-based sampling clock offset estimation method is proposed with greatly decreased estimation delay time. A sampling clock adjusting model in time domain is proposed as well. Simulations and numerical analysis verify better mean square error performance of the proposed method and adjusting model in contrast to the conventional sampling clock synchronization methods. In addition, three types of methods to further improve the sampling clock offset estimation accuracy in burst packet transmission systems are simulated and analyzed with some conclusions drawn.

Time‐of‐flight prediction for fermentation process monitoring

AbstractThis work presents an ultrasound‐based inline sensor system, which is used to monitor the alcoholic yeast fermentation. The pulse‐echo method is used to determine ultrasound velocity (USV) of the sample medium. The major aim of the paper is to highlight the importance of an accurate time‐of‐flight (TOF) estimation for accurate concentration determination and to present method immanent strategies to fulfill the requirements. An algorithm aiming at a stable and highly accurate TOF estimation in time domain was developed. The basic methods of the algorithm are a frame‐wise signal analysis based on the sensor dimensions, cross‐correlation to find complementary impulses and root estimation via polynomial fit to calculate the TOF in time domain. The analysis results of laboratory‐scale validation trials (demineralized, vented water) and of real process data (yeast propagation) are presented. In spite of the stable algorithm performance in the lab scale, the algorithm fails in a few cases of real process signals. The relevant signals and corresponding causes for failure were analyzed and future strategies for algorithm enhancement are discussed. Reviewing the results, the aimed USV accuracy of 0.075 m/s can be achieved. The maximum USV error of the used principles and applied methods in the investigated temperature range is ±0.02%.

Order Estimation of Multivariate ARMA Models

Model order estimation is fundamental in the system identification process. In this paper, we generalize a previous multivariate autoregressive (AR) model order estimation method (J. Lardies and N. Larbi, ?A new method for model order selection and model parameter estimation in time domain,? J. Sound Vibr., vol. 245, no. 2, 2001) to include multivariate autoregressive moving average (ARMA) models and propose a modified model order selection criterion. We discuss the performance analysis of the proposed criterion and show that it has a lower error probability for model order selection when compared to the criterion of G. Liang ?ARMA model order estimation based on the eigenvalues of the covariance matrix,?IEEE Trans. Signal Process., vol. 41, no. 10, pp. 3009-03009, Oct. 1993). A Monte-Carlo (MC) analysis of the model order selection performance under different noise variations and randomized model parameters is performed, allowing the MC results to be generalized across model parameter values and various noise levels. Finally we validate the model for both simulated data and real electroencephalographic (EEG) data by spectral fitting, using the model order selected by the proposed technique as compared to that selected by Akaike's Information Criterion (AIC). We demonstrate that with the proposed technique a better fit is obtained.

Multiscale estimation of the Freundlich adsorption isotherm

Adsorption plays an important role in water and wastewater treatment. The analysis and design of processes that involve adsorption rely on the availability of isotherms that describe these adsorption processes. Adsorption isotherms are usually estimated empirically from measurements of the adsorption process variables. Unfortunately, these measurements are usually contaminated with errors that degrade the accuracy of estimated isotherms. Therefore, these errors need to be filtered for improved isotherm estimation accuracy. Multiscale wavelet based filtering has been shown to be a powerful filtering tool. In this work, multiscale filtering is utilized to improve the estimation accuracy of the Freundlich adsorption isotherm in the presence of measurement noise in the data by developing a multiscale algorithm for the estimation of Freundlich isotherm parameters. The idea behind the algorithm is to use multiscale filtering to filter the data at different scales, use the filtered data from all scales to construct multiple isotherms and then select among all scales the isotherm that best represents the data based on a cross validation mean squares error criterion. The developed multiscale isotherm estimation algorithm is shown to outperform the conventional time-domain estimation method through a simulated example.

Time-Domain Estimation of Time-Varying Channels in OFDM Systems

This letter deals with the time-domain estimation of time-varying channels in orthogonal frequency-division multiplexing (OFDM) systems. The general complex exponential basis expansion model (GCE-BEM) is used to capture the time variation of the channel within an OFDM block. The design criterion of optimal training for OFDM systems in time-varying channels is derived. This optimal training enables the complete elimination of the interference from data symbols and minimizes the noise effect on channel estimation. The design criterion can be used for both pilot symbol aided modulation (PASM) and superimposed training OFDM systems over time-varying channels.

Improved Estimation of the Langmuir Adsorption Isotherm Using Multiscale Filtering

Adsorption isotherms play an important role in the design and analysis of adsorption processes. These isotherms are estimated empirically from measurements of adsorption process variables. Unfortunately, these measurements are usually contaminated with errors that degrade the accuracy of estimated isotherms. Therefore, these errors need to be filtered for improved isotherm estimation accuracy. Multiscale wavelet-based filtering has been shown to be a powerful filtering tool. In this work, multiscale filtering is utilized to improve the estimation accuracy of the Langmuir adsorption isotherm in the presence of measurement noise in the data by developing a multiscale isotherm estimation algorithm. The idea behind the algorithm is to use multiscale filtering to filter the data at different scales, use the filtered data from all scales to construct multiple isotherms, and then select among all scales the isotherm that best represent the data based on a cross-validation mean squares error criterion. The developed multiscale isotherm estimation algorithm is shown to outperform the conventional time-domain estimation method through a simulated example.

Improved, Approximate, Time-Domain ML Estimators of Chirp Signal Parameters and Their Performance Analysis

We derive an improved, approximate, maximum likelihood (ML) estimator for the parameters of a single-component chirp signal in the time domain, which has much lower computational complexity than that of the traditional estimators in the frequency domain. We term it the zero-order amplitude weighted phase-based estimator (AWPE). It is a weighted linear combination of the phases of the received signal samples, where the weights are determined by the amplitudes of the received signals. It achieves better performance than the only existing time-domain estimator in the literature that only exploits the phase information. A phase unwrapping (PU) algorithm is needed to recover the phase information correctly from the received signal samples. Several PU algorithms are compared and analyzed. A new, robust PU algorithm based on the first-order phase differences of the consecutive received signal samples is proposed. This new unwrapping algorithm has smaller PU failure probability than that based directly on the phases of the received signal samples. The need for PU can even be removed by using the second-order phase differences of the consecutive received signal samples. Two additional structures for the ML-based AWPE using the phase differences are derived starting from using the zero-order AWPE obtained. The first is based on the first-order phase differences and the second on the second-order phase differences. When the PU algorithm works perfectly, i.e., no phase unwrapping failure occurs, the estimators based on phase differences do not perform as well as the original one based on absolute phase information due to the increased noise variance. This is also applicable when the chirp parameters take on very small values. However, when no knowledge of the ranges of the chirp parameters is available, and the possible PU failures are taken into account, the estimators based on the phase differences could perform better. Performance analysis of the estimators is given based on an improved phase noise model. It is easy to verify that the estimates obtained are unbiased. The cramer-rao lower bound (CRLB) on the mean-square error (MSE) is derived. The MSE performance of the estimators approaches the CRLB at high signal-to-noise ratios. The variance performance of the estimators based on phase differences is analyzed, whose validity is demonstrated by simulation results.

Practical determination of impulse sample power boosting factor in impulse postfix OFDM systems

An impulse postfix OFDM (IP-OFDM) system, which performs channel estimation in time-domain by exploiting the IP instead of pilot tones, has recently been proposed by Chang et al. Although the proposed system can achieve the enhanced bit error rate (BER) performance compared to that of conventional OFDM systems, there is an important peak-to-average power ratio (PAPR) issue of using the IP that needs to be resolved. In this letter, we propose decision criteria for determining the power boosting factor (PBF) of IP in practical IP-OFDM systems with a high power amplifier (HPA). The analysis is performed with two criteria, the complementary cumulative distribution function of signal PAPR and the input back-off to determine the PBF of IP. The best PBF can be the one which gives an equal power to the IP and the rest of the OFDM symbol. From the analytic results, however, the PBF maximizing the power of the IP out of the HPA turns out to be the best one due to the non-linearities of the HPA. Simulation results demonstrate the effectiveness of the proposed decision criteria for IP-OFDM systems.

Robust Wavelet-Domain Estimation of the Fractional Difference Parameter in Heavy-Tailed Time Series: An Empirical Study

We investigate the performance of several wavelet-based estimators of the fractional difference parameter. We consider situations where, in addition to long-range dependence, the time series exhibit heavy tails and are perturbed by polynomial and change-point trends. We make detailed study of a wavelet-domain pseudo Maximum Likelihood Estimator (MLE), for which we provide an asymptotic and finite-sample justification. Using numerical experiments, we show that unlike the traditional time-domain estimators, estimators based on the wavelet transform are robust to additive trends and change points in mean, and produce accurate estimates even under significant departures from normality. The Wavelet-domain MLE appears to dominate a regression-based wavelet estimator in terms of smaller root mean squared error. These findings are derived from a simulation study and application to computer traffic traces.

Estimation of a nonparametric regression spectrum for multivariate time series

Estimation of a nonparametric regression spectrum based on the periodogram is considered. Neither trend estimation nor smoothing of the periodogram is required. Alternatively, for cases where spectral estimation of phase shifts fails and the shift does not depend on frequency, a time domain estimator of the lag-shift is defined. Asymptotic properties of the frequency and time domain estimators are derived. Simulations and a data example illustrate the methods.

An OFDM Symbol Design for Reduced Complexity MMSE Channel Estimation

In this paper we revisit the minimum mean square error (MMSE) pilot-aided channel estimation for broadband orthogonal frequency division multiplexing (OFDM) systems. The careful design of OFDM symbol leads to the proposal of a simplified time-domain (TD) MMSE estimator. By exploring the Fourier properties of the symbol, the investigated method eliminates the need to use direct or inverse discrete Fourier transforms (DFT/IDFT) before the channel estimation, by using the TD received symbol samples as the input to the MMSE filter. Moreover, performing the estimation in TD (where the channel impulse response (CIR) energy is mainly limit to a small set of samples), makes way to a simple, nonetheless efficient estimation of the filter parameters. The performance of the channel estimation scheme, using the estimated parameters, presents a tolerable degradation when compared with the ideal situation (a-priori knowledge of the channel correlation and noise variance), while exhibiting a reduced computational load. The feasibility of the investigated method is substantiated by system simulation using indoor and outdoor wireless channel models.