Showing papers on "Volterra series published in 2012"
TL;DR: This new approach eliminates the system bandwidth constraints of the conventional DPD techniques, and it allows users to arbitrarily choose the bandwidth to be linearized in the PA output according to the system requirement without sacrificing performance, which makes the DPD system design much more flexible and feasible.
Abstract: The continuously increasing demand for wide bandwidth creates great difficulties in employing digital predistortion (DPD) for radio frequency (RF) power amplifiers (PAs) in future ultra-wideband systems because the existing DPD system requires multiple times the input signal bandwidth in the transmitter and receiver chain, which is sometimes almost impossible to implement in practice. In this paper, we present a novel band-limited digital predistortion technique in which a band-limiting function is inserted into the general Volterra operators in the DPD model to control the signal bandwidth under modeling, which logically transforms the general Volterra series-based model into a band-limited version. This new approach eliminates the system bandwidth constraints of the conventional DPD techniques, and it allows users to arbitrarily choose the bandwidth to be linearized in the PA output according to the system requirement without sacrificing performance, which makes the DPD system design much more flexible and feasible. In order to validate this idea, a high-power LDMOS Doherty PA excited by various wideband signals, including 100-MHz long-term evolution advanced signals, was tested. Experimental results showed that excellent linearization performance can be obtained by employing the proposed approach. Furthermore, this technique can be applied to other linear-in-parameter models. In future ultra-wideband systems, this new technique can significantly improve system performance and reduce DPD implementation cost.
226 citations
TL;DR: In this paper, a new electronic nonlinearity compensation scheme based on inverse Volterra series transfer function (VSTF) is proposed, which shows 1 dB improvement in Q-factor with a 256 Gb/s polarization-division-multiplexed 16-level quadratic amplitude modulation format.
Abstract: The Volterra series transfer function (VSTF), in which the input-output relationship of a nonlinear system is represented by a series of nonlinear kernel functions, is an elegant tool to model nonlinear systems. The inverse of a nonlinear system can be constructed by analyzing VSTF. We propose a new electronic nonlinearity compensation scheme based on inverse VSTF. We show 1 dB improvement in Q-factor with a 256 Gb/s polarization-division-multiplexed 16-level quadratic amplitude modulation format, and 50% reduction in complexity by lowering the processing rate.
149 citations
TL;DR: In this paper, a nonlinear model predictive control (NMPC) strategy was proposed to manipulate the air flow rate in order to maintain the oxygen excess ratio in a desired value, both for safety and performance reasons.
101 citations
TL;DR: A frequency-domain Volterra series nonlinear equalizer is applied to a 20 Gbaud NRZ-QPSK signal propagated over 1600 km and a 2 dB improvement on the nonlinear tolerance over backward propagation split-step Fourier method is obtained.
Abstract: We address the issue of intra-channel nonlinear compensation using a Volterra series nonlinear equalizer based on an analytical closed-form solution for the 3rd order Volterra kernel in frequency-domain The performance of the method is investigated through numerical simulations for a single-channel optical system using a 20 Gbaud NRZ-QPSK test signal propagated over 1600 km of both standard single-mode fiber and non-zero dispersion shifted fiber We carry on performance and computational effort comparisons with the well-known backward propagation split-step Fourier (BP-SSF) method The alias-free frequency-domain implementation of the Volterra series nonlinear equalizer makes it an attractive approach to work at low sampling rates, enabling to surpass the maximum performance of BP-SSF at 2× oversampling Linear and nonlinear equalization can be treated independently, providing more flexibility to the equalization subsystem The parallel structure of the algorithm is also a key advantage in terms of real-time implementation
98 citations
TL;DR: In this paper, a sparse representation of the Volterra series is explored for aerodynamic induced limit-cycle oscillations, for which identification costs are significantly lower than the identification costs of the full VOLTERRA series.
Abstract: For the past two decades, the Volterra series reduced-order modeling approach has been successfully used for the purpose of flutter prediction, aeroelastic control design, and aeroelastic design optimization. The approach has been less successful, however, when applied to other important aeroelastic phenomena, such as aerodynamically induced limit-cycle oscillations. Similar to the Taylor series, the Volterra series is a polynomial-based approach capable of progressively approximating nonlinear behavior using quadratic, cubic, and higher-order functional expansions. Unlike the Taylor series, however, kernels of the Volterra series are multidimensional convolution integrals that are computationally expensive to identify. Thus, even though it is well known that aerodynamic nonlinearities are poorly approximated by quadratic Volterra series models, cubic and higher-order Volterra series truncations cannot be identified because their identification costs are too high. In this paper, a novel, sparse representation of the Volterra series is explored for which the identification costs are significantly lower than the identification costs of the full Volterra series. It is demonstrated that sparse Volterra reduced-order models are capable of efficiently modeling aerodynamically induced limit-cycle oscillations of the prototypical NACA 0012 benchmark model. These results demonstrate for the first time that Volterra series models are capable of modeling aerodynamically induced limitcycle oscillations.
86 citations
TL;DR: Aiming at the problem to locate parametric faults in nonlinear analog circuits, a new approach based on the subband decomposition combined with coherence functions is proposed, which shows the effectiveness of the method of the fault diagnosis in non linear circuits.
Abstract: Aiming at the problem to locate parametric faults in nonlinear analog circuits, a new approach based on the subband decomposition combined with coherence functions is proposed. First, the Volterra series of the circuit under test decomposed by wavelet packets are used to detect the parametric faults. Then, the Volterra series in subbands are used to calculate the coherence functions. By comparison with the fault signatures, different states of the parametric faulty circuits are identified, and the faults are located. Simulations show the effectiveness of the method of the fault diagnosis in nonlinear circuits.
38 citations
TL;DR: In this article, a nonlinear system identification model based on an adaptive Volterra filter is developed to investigate the inherent nonlinear phenomenon of a parametric acoustic array effect in air, which is the byproduct of nonlinear interaction between the primary waves.
37 citations
TL;DR: This paper deals with the identification of a nonlinear SISO system modelled by a second-order Volterra series expansion when both the input and the output are disturbed by additive white Gaussian noises and suggests solving the identification problem as an errors-in-variables issue by means of the so-called Frisch scheme.
27 citations
TL;DR: This paper proposes a method of digital predistortion suitable for wideband high crest factor applications such as those encountered in DAB, DVB-T and WCDMA transmitters and utilizes a reliable frequency domain measure of transmitter output nonlinearity as the objective forpredistortion filter parameter estimation.
Abstract: This paper proposes a method of digital predistortion suitable for wideband high crest factor applications such as those encountered in DAB, DVB-T and WCDMA transmitters. The proposed method is advantageous for four main reasons. Firstly, it utilizes a reliable frequency domain measure of transmitter output nonlinearity, specifically the Weighted Adjacent Channel Power (WACP), as the objective for predistortion filter parameter estimation. This is in direct contrast to traditional approaches which utilize a time domain measure obtained via a full feedback path and potentially corrupted by gain and phase compensation error as well as ADC distortion. Secondly, the method models predistortion filter parameter estimation as a generic nonlinear mathematical optimization problem. This model assumes a nonconvex objective function and therefore utilizes both global and local optimization algorithms to achieve true global convergence. This is once again in direct contrast to traditional approaches which model predistortion filter parameter estimation as a linear regression problem. Such a model incorrectly assumes a convex error surface and therefore restricts itself to inadequate local optimization algorithms which unfortunately cannot guarantee true global convergence. Thirdly, the method's predistortion filter is a pruned Volterra Series with memory which utilizes a hybrid pruning strategy in order to keep high order kernels to a practically manageable size, suitable for optimization parameter estimation. Predistortion filter memory ultimately makes the method highly suited to wideband applications. Finally, predistortion filter parameter estimation does not require known test signals to be injected into the transmitter and therefore the technique is on-air adaptive. This means any transmitter using this method of digital predistortion will be both on-air and optimally linearized for its entire operational life. Preliminary results obtained from actual hardware are presented.
20 citations
TL;DR: A modified least squares (MLS) method is proposed for DPD coefficients extraction, which can eliminate the detrimental effect of feedback measurement errors without using a post-compensator and achieve comparable performance as the state-of-the-art.
Abstract: Measurement errors (in-phase/quadrature imbalance, dc offset, and nonlinearity) in the feedback path can adversely affect the linearization performance of digital predistorter (DPD) for RF power amplifiers (PAs). In this paper, a generalized analysis for the Volterra-series DPD system is presented in the presence of feedback measurement errors. It shows that the DPD coefficients are biased due to these errors. A modified least squares (MLS) method is then proposed for DPD coefficients extraction, which can eliminate the detrimental effect of feedback measurement errors without using a post-compensator. The proposed MLS method has the advantage of being free of behavioral modeling for the feedback path or the post-compensator. However, it can still achieve comparable performance as the state-of-the-art. The performance of the MLS method is validated with both simulations and experiments. The measurement results show that, when a nonideal feedback path is employed to capture the PA output, the proposed MLS method can still ensure a high linearization performance of the DPD, and the results are nearly the same as that when an ideal feedback path is used.
18 citations
TL;DR: This paper presents long-term nonlinear prediction based on second-order Volterra filters that can outperform conventional linear prediction techniques in terms of prediction gain and “whiter” residuals.
Abstract: Previous studies of nonlinear prediction of speech have been mostly focused on short-term prediction. This paper presents long-term nonlinear prediction based on second-order Volterra filters. It will be shown that the presented predictor can outperform conventional linear prediction techniques in terms of prediction gain and “whiter” residuals.
TL;DR: A generative statistical modeling method for detecting nonlinear generalized synchronization using Truncated Volterra series to approximate functional interactions and its experimental applicability is demonstrated by detecting non linear interactions between neuronal local field potentials recorded in different parts of macaque visual cortex.
Abstract: Detecting nonlinear correlations between time series presents a hard problem for data analysis. We present a generative statistical modeling method for detecting nonlinear generalized synchronization. Truncated Volterra series are used to approximate functional interactions. The Volterra kernels are modeled as linear combinations of basis splines, whose coefficients are estimated via ${l}_{1}$ and ${l}_{2}$ regularized maximum likelihood regression. The regularization manages the high number of kernel coefficients and allows feature selection strategies yielding sparse models. The method's performance is evaluated on different coupled chaotic systems in various synchronization regimes and analytical results for detecting $m:n$ phase synchrony are presented. Experimental applicability is demonstrated by detecting nonlinear interactions between neuronal local field potentials recorded in different parts of macaque visual cortex.
TL;DR: Fundamental results are established for truncation order and its effect in the Volterra class of nonlinear systems, and this work provides a much improved version of the multi-level excitation method for system analysis and identification.
17 Jun 2012
TL;DR: In this article, a band-limited Volterra series-based behavioral model for RF power amplifiers is proposed, which is achieved by inserting a bandlimiting function in the time domain into the VOLTERRA operators to control the bandwidth of the output signal being modeled.
Abstract: In this paper, a new band-limited Volterra series-based behavioral model for RF power amplifiers is proposed. It is achieved by inserting a band-limiting function in the time domain into the Volterra operators to control the bandwidth of the output signal being modeled, which provides a simple and logical way to transform general Volterra series-based models into band-limited versions. An LDMOS Doherty power amplifier excited by a 60 MHz 12-carrier WCDMA signal is tested to validate this approach. Experimental results show that the new approach provides much higher accuracy when mapping the band-limited input to the band-limited output of the power amplifier. This approach can be applied to any Volterra-based behavioral models, and provides a very promising solution for wideband digital predistortion of RF power amplifiers especially in the context of future ultra wideband wireless systems.
TL;DR: In this article, a new nonparametric routine is proposed to extend the capability of Volterra analysis in the frequency domain to weakly nonlinear Duffing systems at a much wider range of excitation amplitude range which the current underlying nonlinear differential equation models fail to address.
18 Jul 2012
TL;DR: The proposed quadratic edge detection filter can account for much of the polynomial nonlinearities inherent in the input mammogram image and can replace the conventional edge detectors like Laplacian, gaussian etc.
Abstract: The paper summarizes the design and implementation of a quadratic edge detection filter, based on Volterra series, for enhancing calcifications in mammograms. The proposed filter can account for much of the polynomial nonlinearities inherent in the input mammogram image and can replace the conventional edge detectors like Laplacian, gaussian etc. The filter gives rise to improved visualization and early detection of microcalcifications, which if left undetected, can lead to breast cancer. The performance of the filter is analyzed and found superior to conventional spatial edge detectors.
TL;DR: The Wiener–Hammerstein Benchmark is identified as a bilinear discrete system using an iterative bilInear subspace identification algorithm previously proposed by the authors and polynomial static nonlinearities were added to the bilinEAR model input.
25 Mar 2012
TL;DR: This paper focuses on digital post compensation of nonlinear analog-to-digital converters (ADCs) and proposes a blind linearization approach based on the Volterra series, which demonstrates the effectiveness of the proposed method.
Abstract: Blind Volterra system linearization is a challenging problem with a variety of applications where nonlinearities are present and training signals are not. This paper focuses on digital post compensation of nonlinear analog-to-digital converters (ADCs) and proposes a blind linearization approach based on the Volterra series. Assuming that the input signal does not occupy the full Nyquist bandwidth, i.e., there exists an energy-free band, the Volterra series coefficients are estimated by minimizing the linearized signal power in the energy-free band. Simulation results are presented which demonstrate the effectiveness of the proposed method.
TL;DR: The results obtained show that the RC cell nonlinearities composing the hydropneumatic networks of the CRONE suspension do not modify the stability degree robustness versus sprung mass variations, thus extending in a nonlinear context this robustness that is present in the linear context.
Abstract: This paper presents a fractional system composed of a sprung mass and a suspension device with fractional impedance (fractance for short). More precisely, this fractance is a fractional integrator. Practical realizations of this fractional integrator based on hydropneumatic RC cells are presented in a limited frequency band. The main objective of this paper is to analyze the influence of the hydropneumatic RC cell nonlinearities, which constitute the hydropneumatic networks of the CRONE suspension, on the stability degree robustness when varying the sprung mass. First, the achievement of a nonlinear validation model is emphasized, and then, a linear synthesis model is presented. These two models are used in the second part of this paper to analyze the obtained performances and to show the influence of the nonlinearities. This analysis of performances is made first from a qualitative standpoint using the functional domain of each Ri and Ci element and then from the quantitative standpoint using the Volterra series. In fact, the difference between the response of the nonlinear model and the one of the first-order kernel (which represents the linear response of the system) allows the determination of the influence of the nonlinearities on the dynamic behavior for a particular signal input. The results obtained show that the RC cell nonlinearities composing the hydropneumatic networks of the CRONE suspension do not modify the stability degree robustness versus sprung mass variations, thus extending in a nonlinear context this robustness that is present in the linear context.
17 Jun 2012
TL;DR: In this paper, the pruning of Volterra series used to linearize power amplifiers (PAs) exhibiting memory effects has been discussed and applied to synthesize a digital predistortion (DPD) function.
Abstract: This paper expounds on the pruning of Volterra series used to linearize power amplifiers (PAs) exhibiting memory effects. This pruning approach starts with the identification of the minimum set of dominant kernels needed in the Volterra series modeling for a given PA. The pruned Volterra series is then applied to synthesize a digital predistortion (DPD) function. The proposed pruned Volterra series DPD achieved more than 50 dBc ACPR and −38 dB EVM when a 45 Watts GaN PA at 2.14 GHz was driven by a 20 MHz WCDMA signal. In addition, the proposed model was found to lead to reduced span of the kernels values and better numerical conditioning.
14 Feb 2012
TL;DR: Moideen et al. as discussed by the authors developed tools to predict parametric roll motion of ships in regular and irregular sea and provide guidelines to avoid parametric rolling during initial design stage.
Abstract: Prediction of Parametric Roll of Ships in Regular and Irregular Sea. (December 2010) Hisham Moideen, B.Tech, Cochin University of Science and Technology, India Chair of Advisory Committee: Dr. Jeffrey M. Falzarano This research was done to develop tools to predict parametric roll motion of ships in regular and irregular sea and provide guidelines to avoid parametric roll during initial design stage. A post Panamax hull form (modified C11 Hull form, Courtesy of MARIN) was used to study parametric roll in ships. The approach of the study has been to simplify the roll equation of motion to a single degree of freedom equation so as to utilize the tools available to analyze the system retaining the non-linear character of the system. The Hill’ equation is used to develop highly accurate stability boundaries in the Ince-Strutt Diagram. The effect of non-linear damping has also been incorporated into the chart for the first time providing a simple method to predict the bounded roll motion amplitude. Floquet theory is also extended to predict parametric roll motion amplitude. Forward speed of the vessel has been treated as a bifurcation parameter and its effects studied both in head and following sea condition. In the second half of the research, parametric roll of the vessel in irregular sea is investigated using the Volterra Quadratic model. GM variation in irregular sea was
13 Aug 2012
TL;DR: In this article, the authors present a phenomenological and mathematically rigorous approach to nonlinear modeling of the unsteady aerodynamics based on Volterra variational equations, which consists of dierential equations of internal states corresponding to dierent kernels of the VOLTERRA series.
Abstract: The aerodynamics at high-angle-of-attack is an unsteady and nonlinear phenomena in time. In this paper, we present a phenomenological and mathematically rigorous approach to nonlinear modeling of the unsteady aerodynamics based on Volterra variational equations. The model consists of dierential equations of internal states corresponding to dierent kernels of the Volterra series. The model structure is generic as the number of states can be chosen contingent on available wind tunnel test data and delity of the model desired. Model parameters are estimated using forced oscillation wind tunnel test data. We present modeling of the normal force coecient of a delta-wing aircraft. We nd that two-states are sucient for accurate modeling of the normal force coecient in small and large amplitude oscillations in pitch at dierent frequencies. We show that the model is consistent with various experimental observations reported in literature. In the end we compare it with other models proposed in literature.
TL;DR: In this article, a novel approach based on fractional correlation is proposed and the application of the subband Volterra series is used in the diagnosis of incipient faults in nonlinear analog circuits.
Abstract: Considering the problem to diagnose incipient faults in nonlinear analog circuits, a novel approach based on fractional correlation is proposed and the application of the subband Volterra series is used in this paper. Firstly, the subband Volterra series is calculated from the input and output sequences of the circuit under test (CUT). Then the fractional correlation functions between the fault-free case and the incipient faulty cases of the CUT are derived. Using the feature vectors extracted from the fractional correlation functions, the hidden Markov model (HMM) is trained. Finally, the well-trained HMM is used to accomplish the incipient fault diagnosis. The simulations illustrate the proposed method and show its effectiveness in the incipient fault recognition capability.
16 Sep 2012
TL;DR: Experimental demonstration of a dual-polarization Volterra series nonlinear equalizer applied in frequency-domain is carried out for 100G polarization-multiplexed QPSK test signals, and the BER is reduced by a factor of ~2.5× relatively to the single-Polarization approach, with 1 dB increase in the optimum power.
Abstract: Experimental demonstration of a dual-polarization Volterra series nonlinear equalizer applied in frequency-domain is carried out for 100G polarization-multiplexed QPSK test signals. We were able to reduce the BER by a factor of ~2.5× relatively to the single-polarization approach, with a 1 dB increase in the optimum power.
01 Jan 2012
TL;DR: In this article, a method for identifying the Volterra kernels is developed by applying Wavelet Network, which is applied for the analysis of nonlinear nonstationary time series.
Abstract: Volterra series representation is the earliest method for the description of a nonlinear system. Volterra kernels completely characterize the Volterra series. Volterra series has been extended to incorporate the non stationarity. Even though Volterra series modeling was suggested much earlier, no canonical method for the identification of the Volterra kernel was available due to the exponential growth of parameters in the kernel with the order of expansion. Developments in the theories of Artificial Neural Networks and Wavelets gave rise to the concept of Wavelet Networks which are found to be effective in modeling the nonlinear nonstationary structures. In this paper a method for identifying the Volterra kernels is developed by applying Wavelet Network. Thereby the Volterra series is applied for the analysis of nonlinear nonstationary time series providing a powerful method in the analysis of nonlinear nonstationary time series, which appear quite often in various
TL;DR: This paper compares alternatives to reduce the complexity, number of operations, and the time in the linearization of PA through DPD measured with the OFDM signal to show that the VSS algorithm is faster and e_ective to calculate the parameters in the Volterra model.
04 Mar 2012
TL;DR: In this paper, the performance of a nonlinear compensation scheme based on the Volterra Series on a 224 Gb/s PolMux-16QAM system over 250 km of fiber was evaluated.
Abstract: We demonstrate the performance of a nonlinear compensation scheme based on the Volterra Series on a 224 Gb/s PolMux-16QAM system over 250 km of fibre and comment on its improvement in performance over linear equalization.
TL;DR: This letter focuses on the a posteriori correction of Volterra-Laguerre models in order to meet specific static or dynamic requirements.
Abstract: This letter focuses on the a posteriori correction of Volterra-Laguerre models in order to meet specific static or dynamic requirements. The authors set a general theoretical framework and provide an illustrative example.
TL;DR: A new dynamic non-linear MISO system model using discrete-time Volterra series to provide a reduced complexity model and develops two new general approaches based on Gauss-Newton and exhaustive algorithms.
Abstract: In this paper, we propose a new dynamic non-linear MISO system model using discrete-time Volterra series. To provide a reduced complexity model, each Volterra kernel is expanded on independent generalised orthonormal bases (GOBs) associated to the inputs to develop a new black-box non-linear MISO-GOB-Volterra model. However, this reduction is ensured once the poles characterising each independent generalised orthonormal basis (GOB) are set to their optimal values. For the selection of optimal GOBs poles, we develop two new general approaches based on Gauss-Newton and exhaustive algorithms, the performances of which are illustrated and compared in simulation.
25 Oct 2012
TL;DR: In this paper, a continuous surfacepotential-based electro-thermal compact model suitable for the study of intermodulation distortion IMD in GaAs HEMT devices is presented.
Abstract: We present a continuous surface-potential- based electro-thermal compact model suitable for the study of intermodulation distortion IMD in GaAs HEMT devices. We have developed a precise analytical calculation for the position of the Fermi level Ef in these devices from a consistent solution of Schrodinger's and Poisson's equations. The accuracy of our calculation is of the order of pico-volts. Ef is used to define the surface-potential ψ and subsequently derive the drain current Id. We use the developed Id model for prediction of IMD in these devices using Volterra series method. The model is in excellent agreement with experimental IMD data. The impact of various real device effects like self- heating, mobility degradation etc., on the non- linear behavior of the device is analyzed using the model.