Nonlinear Echo Research Articles

Suppression of remnant nonlinear echo due to harmonic distortions in intelligent communication networks

Voice communication today has become an important and an integral part of human kind in which speech quality is an important concern. The issue of speech degradation due to end user devices can be tackled when efficient devices and algorithms are used to cancel acoustic echo. Acoustic echo canceller (AEC) is used to eliminate unwanted echo which dampens speech signal and reduces the efficiency of signal transmission. With advent of sophisticated technology low cost loudspeakers and power amplifiers are devised which bring nonlinearity into communication channel. In this paper, an improved solution for the cancellation of the nonlinear echo to restore the speech quality in a communication channel is designed. The conceived algorithm deals with nonlinear AEC with moderately low computational complexity and faster convergence. The whole process starts with linear AEC and then the proposed harmonic distortion nonlinear remnant echo suppressor comes into action after passing through linear AEC.

Nonlinear Acoustic Echo Cancellation by Exact-Online Adaptive Alternating Minimization

Nonlinear Acoustic Echo Cancellation by Exact-Online Adaptive Alternating Minimization

A Bayesian network approach to linear and nonlinear acoustic echo cancellation

This article provides a general Bayesian approach to the tasks of linear and nonlinear acoustic echo cancellation (AEC). We introduce a state-space model with latent state vector modeling all relevant information of the unknown system. Based on three cases for defining the state vector (to model a linear or nonlinear echo path) and its mathematical relation to the observation, it is shown that the normalized least mean square algorithm (with fixed and adaptive stepsize), the Hammerstein group model, and a numerical sampling scheme for nonlinear AEC can be derived by applying fundamental techniques for probabilistic graphical models. As a consequence, the major contribution of this Bayesian approach is a unifying graphical-model perspective which may serve as a powerful framework for future work in linear and nonlinear AEC.

Nonlinear Acoustic Echo Cancellation Using Voltage and Current Feedback

Acoustic echo cancellation (AEC) is a well studied problem. The underlying assumption in most echo cancellation solutions is that the echo path following the reference signal is completely linear. However, in many handheld devices, the echo path following the reference signal is nonlinear. The reason for this nonlinearity in the echo path is the use of smaller inexpensive loudspeakers and the desire for generating high sound pressure levels. This brings about the need for a nonlinear echo canceler to maintain the required echo return loss enhancement (ERLE). Many software-based solutions have been proposed to solve this problem, but the computational complexity of these solutions is prohibitively high for practical implementation. This paper analyzes the sources of nonlinearities in smartphones and proposes a simple, elegant hardware modification to significantly reduce nonlinear echo. Thorough analysis and intensive testing results show that up to 6 dB of improvement in ERLE in a real device is possible using the proposed technique.

Error-dependent step-size control of adaptive normalized least-mean-square filters used for nonlinear acoustic echo cancellation

This paper proposes novel acoustic echo cancellation (AEC) approaches based on linear and Volterra structures. The AECs use modified normalized least-mean-square (NLMS) updates to improve the convergence and to maintain the same steady-state misadjustment. In the first case, starting from a new cost function, the resulting variable step size depends on the instant error value and on an estimated error threshold. Secondly, the need of beforehand steady-state error threshold estimation is removed by an automatic step-size control involving the absolute error envelope evolution. The methods are tested for an acoustic enclosure setup modeled using measured linear and quadratic kernels, and their behavior is compared to that of the traditional NLMS and another technique found in the open literature. Also, they are tested for a change in the echo path and for assorted nonlinearity and local signal powers. The comparison is made in terms of the echo-return loss enhancement for WGN and speech as excitation. The simulations show that the proposed adaptations offer increased convergence rates for the same steady-state error.

Frequency-Domain Volterra Filter Based on Data-Driven Soft Decision for Nonlinear Acoustic Echo Suppression

In this letter, we propose a novel frequency-domain second-order Volterra filter based on soft decision for nonlinear acoustic echo suppression. This letter offers an efficient algorithm for nonlinear echo power estimation using the second-order Volterra filter and an AES algorithm using the estimated nonlinear echo power spectrum within a soft decision baseline by incorporating the ratio of the a priori probability of near-end speech presence and absence, which is obtained by using a data-driven training method.

Nonlinear Acoustic Echo Suppression Based on Spectrum Selection Using the Amount of Linear Echo Cancellation

Nonlinear Acoustic Echo Suppression Based on Spectrum Selection Using the Amount of Linear Echo Cancellation

Least Squares 기반의 Volterra Filter를 이용한 비선형 반향신호 억제기

기존의 반향신호 억제기는 스피커와 마이크 사이의 선형 관계만을 고려하여, 마이크로 입력된 신호로 부터 반향신호를 억제한다. 하지만 실제적으로 스피커는 비선형성을 가지고 있으며, 이 때문에 기존의 반향신호 억제기는 비선형 반향신호 환경에서 그 성능이 저하된다. 본 논문에서는 스피커의 비선형성을 모델링하기에 적합한 주파수영역상의 Least square 방식의 Volterra filter를 적용한 비선형 반향신호 억제기를 제안하였다. 객관적 성능평가 방법인 Echo Return Loss Enhancement (ERLE)와 Speech Attenuation(SA)를 도입하여 제안된 알고리즘의 성능 검증에 사용하였다. 제안된 알고리즘이 기존의 반향신호 억제기보다 선형 및 비선형 반향신호 환경에서 우수한 성능을 보이는 것을 확인하였다.

Enhanced Adaptive Volterra Filtering by Automatic Attenuation of Memory Regions and Its Application to Acoustic Echo Cancellation

This paper presents a novel scheme for nonlinear acoustic echo cancellation based on adaptive Volterra Filters with linear and quadratic kernels, which automatically prefers those diagonals contributing most to the output of the quadratic kernel with the goal of minimizing the overall mean-square error. In typical echo cancellation scenarios, not all coefficients will be equally relevant for the modeling of the nonlinear echo, but coefficients close to the main diagonal of the second-order kernel will describe most of the nonlinear echo distortions, such that not all diagonals need to be implemented. However, it is difficult to decide the most appropriate number of diagonals a priori, since there are many factors that influence this decision, such as the energy of the nonlinear echo, the shape of the room impulse response, or the step size used for the adaptation of kernel coefficients. Our proposed scheme incorporates adaptive scaling factors that control the influence of each group of adjacent diagonals contributing to the quadratic kernel output. An appropriate selection of these factors serves to emphasize or neglect diagonals of the model as required by the present situation. We provide adaptation rules for these factors based on previous works on combination of adaptive filters, and comprehensive simulations showing the reduced gradient noise reached by the new echo canceller.

Exploiting Group Sparsity in Nonlinear Acoustic Echo Cancellation by Adaptive Proximal Forward-Backward Splitting

Exploiting Group Sparsity in Nonlinear Acoustic Echo Cancellation by Adaptive Proximal Forward-Backward Splitting

A 48-Port FCC-Compliant 10GBASE-T Transmitter With Mixed-Mode Adaptive Echo Canceller

High density 48-port network switches demand very power-efficient, small form-factor physical layer transceivers which comply with the transmit PSD and return loss requirements, on the one hand, and meet the FCC Class-A specifications on the other hand, while achieving better than 10E-12 BER. The presented 10GBASE-T transmitter and hybrid utilize a current-mirroring amplifier with output rise-time control and high CMRR to perform a first-order linear and nonlinear echo cancellation while enabling the design of 48-port FCC compliant network switches. Experimental results over the 400-MHz bandwidth exhibit a worst case transmitter linearity of >;57 dBc as well as worst case post-hybrid fundamental and SFDR power of -18 and -70 dBc, respectively, across the 400-MHz frequency range of interest. The echo fundamental component is further attenuated to <; -60 dB in the analog domain by an adaptive mixed-mode echo canceller. Implemented in a 40-nm CMOS technology, the transmitter plus hybrid consumes 200 mW power and occupies 0.5 mm2.

State-Space Frequency-Domain Adaptive Filtering for Nonlinear Acoustic Echo Cancellation

In this paper, we address adaptive acoustic echo cancellation in the presence of an unknown memoryless nonlinearity preceding the echo path. We approach the problem by considering a basis-generic expansion of the memoryless nonlinearity. By absorbing the coefficients of the nonlinear expansion into the unknown echo path, the cascade observation model is transformed into an equivalent multichannel structure, which we further augment with a multichannel first-order Markov model. For the resulting multichannel state-space model, we then derive a recursive Bayesian estimator that takes the form of an adaptive Kalman algorithm in the discrete Fourier transform (DFT) domain. We show that such a recursive estimator can be realized via a stable and structurally efficient multichannel state-space frequency-domain adaptive filter. We demonstrate that our algorithm, which stems from a contained framework, provides effective nonlinear echo cancellation in the presence of continuous double-talk, varying degree of nonlinear distortion, and changes in the echo path.

Laser Radar Range-Doppler Imaging and Simulation on High-speed Target

On the basic of the representation of the principle of Doppler imaging, an echo model of high-speed target illuminated by broadband linear frequency modulated (LFM) signal was established in this paper. For high-speed target, because of its nonlinear echo phase and time-varying Doppler frequency shift, the Doppler spectrum of the target acquired by the traditional Fourier method was ambiguous, and the same in the radar images of the target. Therefore, an adaptive Wigner-Ville time-frequency analysis method was presented in the paper, that is, the local fuzzy function could be obtained by applying the two-dimensional adding Window Fourier Transform to signal's Wigner-Ville distribution, which made the kernel function, not only be adaptive to time, but also to the frequency. Finally, the simulation results show that the method has a good time-frequency concentration, and effectively control the cross-term interference.

Adaptive Combination of Volterra Kernels and Its Application to Nonlinear Acoustic Echo Cancellation

The combination of filters concept is a simple and flexible method to circumvent various compromises hampering the operation of adaptive linear filters. Recently, applications which require the identification of not only linear, but also nonlinear systems are widely studied. In this paper, we propose a combination of adaptive Volterra filters as the most versatile nonlinear models with memory. Moreover, we develop a novel approach that shows a similar behavior but significantly reduces the computational load by combining Volterra kernels rather than complete Volterra filters. Following an outline of the basic principles, the second part of the paper focuses on the application to nonlinear acoustic echo cancellation scenarios. As the ratio of the linear to nonlinear echo signal power is, in general, a priori unknown and time-variant, the performance of nonlinear echo cancellers may be inferior to a linear echo canceller if the nonlinear distortion is very low. Therefore, a modified version of the combination of kernels is developed obtaining a robust behavior regardless of the level of nonlinear distortion. Experiments with noise and speech signals demonstrate the desired behavior and the robustness of both the combination of Volterra filters and the combination of kernels approaches in different application scenarios.

Maneuvering Multi-target Tracking Algorithm Based on Modified Generalized Probabilistic Data Association

Aiming at the problem of strong nonlinear and effective echo confirm of multi-target tracking system in clutters environment, a novel maneuvering multitarget tracking algorithm based on modified generalized probabilistic data association is proposed in this paper. In view of the advantage of particle filter which can deal with the nonlinear and non-Gaussian system, it is introduced into the framework of generalized probabilistic data association to calculate the residual and residual covariance matrices, and the interconnection probability is further optimized. On that basis, the dynamic combination of particle filter and generalized probabilistic data association method is realized in the new algorithm. The theoretical analysis and experimental results show the filtering precision is obviously improved with respect to the tradition method using suboptimal filter.

TU‐D‐201C‐01: Physics in the Evolution of Contrast Agents in Ultrasound

The acoustic bubble has graduated from an intriguing curiosity in physics to the center stage of ultrasound imaging in clinical medicine. This is principally a consequence of the development of a new generation of bubble constructs ‐ heavy gases stabilized by a shell of lipid or other biocompatible material ‐ that have been approved as intravenous contrast agents for diagnostic medicine. The bubbles are smaller than a red blood cell and so pass freely around the circulation. By a serendipity, they happen to resonate at frequencies within the diagnostic range, and so can be driven easily into nonlinear oscillation by a typical ultrasound imaging pulse. This has spawned a mass of nonlinear echo detection strategies that are now sufficiently sensitive to detect an individual 3 micron bubble flowing in a capillary more than 10 cm below the skin surface, while rejecting echoes from tissue. The resulting real time perfusion images have redefined what is possible to diagnose from a medical ultrasound image. This talk will explore the bubbles and their acoustic behavior, the nonlinear imaging methods to detect them and their applications in medicine. Foremost among these is the ability to detect the microvessels that accompany the growth of a cancer ‐ malignant angiogenesis ‐ and, by disrupting the bubbles remotely using the ultrasound beam, to measure blood flow at the tissue level, an important indicator of response to therapy. In their current form, the bubbles flow in the vascular system without interacting with it, but it is easy to modify their surface so that they bind to specific cellular or molecular targets on the endothelial cells lining blood vessels. Such biomarkers assure ultrasound a place in the effort to create an imaging method of the future that provides functional information about the patient at a molecular, as well as a macroscopic level.

Modeling and detecting localized nonlinearity in continuum systems with a multistage transform

A general method is presented for modeling spatially extended systems that may contain a localized source of nonlinearity. It has direct applications to structural health monitoring (SHM) where physical damage may cause such nonlinearity and also communications channels which may exhibit localized nonlinearity due to bad electrical contacts or component nonlinearity. The method uses a multistage nonlinear transform in order to model the system dynamics. We discuss the application to SHM and provide a preliminary test of the method with experimental data from a randomly shaken beam with loose bolts. We discuss the application to telecommunications, provide an experimental observation of symmetric nonlinearity in a "bad" electrical contact, and provide a preliminary test of using this method to remove nonlinear echo (and thereby improve data rate) on a telephone line used for data transmission.

DTD-free nonlinear acoustic echo cancellation based on independent component analysis

An adaptive acoustic echo cancellation method based on independent component analysis, which can remove nonlinear echo components, is presented. Since this method takes into account the independence between a far-end signal and the echo-cancelled output to cancel acoustic echoes which are independent of near-end signals, it can continue to update AEC parameters even in double-talk situations, thereby improving the cancellation performance. Experiments show that the proposed method provides better performance than the conventional least-mean-square methods for both linear and nonlinear AEC systems without requiring separate double-talk detection (DTD).

A Nonlinear Acoustic Echo Canceller Using Sigmoid Transform in Conjunction With RLS Algorithm

Nonlinearity of amplifiers and/or loudspeakers gives rise to nonlinear echo in acoustic systems, which seriously degrades the performance of speech and audio communications. Many nonlinear acoustic echo cancellation (AEC) methods have been proposed. In this paper, a simple yet efficient nonlinear echo cancellation scheme is presented by using an adaptable sigmoid function in conjunction with a conventional transversal adaptive filter. The new scheme uses the least mean square (LMS) algorithm to update the parameters of sigmoid function and the recursive least square (RLS) algorithm to determine the coefficient vector of the transversal filter. The proposed AEC is proved to be convergent under some mild assumptions. Computer simulations show that the proposed scheme gives a superior echo cancellation performance over the well known Volterra filter approach when the echo path suffers from the saturation-type nonlinear distortion. More importantly, the new AEC has a much lower computational complexity than the Volterra-filter-based method.

Suppression of tissue harmonics for pulse-inversion contrast imaging using time reversal

Pulse-inversion (PI) sequences are sensitive to the nonlinear echoes from microbubbles allowing an improvement in the blood-to-tissue contrast. However, at larger mechanical indices, this contrast is reduced by harmonics produced during nonlinear propagation. A method for tissue harmonics cancellation exploiting time reversal is experimentally implemented using a 128-channel 12-bit emitter receiver. The probe calibration is performed by acquiring the nonlinear echo of a wire in water. These distorted pulses are time-reversed, optimized and used for the PI imaging of a tissue phantom. Compared to normal (straight) pulses, the time-reversed distorted pulses reduced the tissue signal in PI by 11 dB. The second harmonic signals from microbubbles flowing in a wall-less vessel were unaffected by the correction. This technique can thus increase the blood-to-tissue contrast ratio while keeping the pressure and the number of pulses constant.