LMS-LMF adaptive scheme for echo cancellation

The authors present a novel algorithm for echo cancellation. The algorithm consists of simultaneously applying the LMS algorithm to the near-end section of the echo canceller, and a controlled mixed LMS-LMF algorithm to the far-end section. This combination results in a substantial improvement in performance of the proposed scheme over the LMS and the LMF algorithms     

Proportionate adaptive algorithms for network echo cancellation

By analyzing the coefficient adaptation process of the steepest descent algorithm, the condition under which the fastest overall convergence will be achieved is obtained and the way to calculate optimal step-size control factors to satisfy that condition is formulated. Motivated by the results and using the stochastic approximation paradigm, the /spl mu/-law PNLMS (MPNLMS) algorithm is proposed to keep, in contrast to the proportionate normalized least-mean-square (PNLMS) algorithm, the fast initial convergence during the whole adaptation process in the case of sparse echo path identification. Modifications of the MPNLMS algorithm are proposed to lower the computational complexity.     

Asynchronous VLSI architecture for adaptive echo cancellation

A single chip, 128 coefficient, asynchronous echo canceller is presented. Cancellation is performed by an FIR filter whose coefficients are adapted using the power-of-two modified LMS algorithm. The pipelined circuit updates all coefficients and generates the filtered output every cycle while allowing a sampling rate >206.5 kHz     

Hybrid LMS-LMF algorithm for adaptive echo cancellation

The coefficients of an echo canceller with a near-end section and a far-end section are usually updated with the same updating scheme, such as the LMS algorithm. A novel scheme is proposed for echo cancellation that is based on the minimisation of two different cost functions, i.e. one for the near-end section and a different one for the far-end section. The approach considered leads to a substantial improvement in performance over the LMS algorithm when it is applied to both sections of the echo canceller. The convergence properties of the algorithm are derived. The proposed scheme is also shown to be robust to noise variations. Simulation results confirm the superior performance of the new algorithm     

一种自适应电话会议回波抵消系统

文中给出一种基于去相关最小均方(DLMS)算法和迭代最大长度序列相关(IMLC)算法的电话会议回声抵消系统。鉴于DLMS算法在远端会话期间具有好的工作性能，而IMLC算法在双端会话期间具有良好的工作效果，这种新的回声抵消系统在远端会话期间用DLMS算法估计回声路径，而在双端会话期间用IMLC算法估计回声路径。计算机仿真表明，这种新的回声抵消系统在远端会话和双端会话情况下均能提供较好的回声路径估计。     

通信系统中自适应回波抵消的一种新方法

语音分组传输系统的出现，对回波抵消技术提出了新的挑战。在回波抵消中一个关键的问题是需要快速有效地估计延迟时间。基于直接计算输入信号互相关函数的延迟估计方法，在实际应用中回波消除性能差，运算量大。为此提出了基于混合模型的延时估计方法，对输入信号进行带通滤波和降低抽样率抽样，使其具有白噪声特性，然后快速计算互相关函数的估计值。理论分析和实验结果证明新的延迟估计方法有很好的回波消除性能和较少的运算量，在实际通信系统中有较好的应用前景。     

Frequency-domain adaptive filtering with applications to acoustic echo cancellation

In this paper an algorithm is presented for adaptive filtering in the frequency-domain with application to acoustic echo cancellation. This algorithm, called generalized multi-delay filter(GMDFα, is derived from the frequency-domain implementation of the time-domain block least mean square algorithm. Two different implementations are introduced, one based on the discrete Fourier transform(dft) and one based on the discrete Hartley transform(DHT); some results on fixed-point implementation of the algorithm are provided which are compared to results obtained from floating point implementation. Finally, the application of thegmdfα algorithm to acoustic echo cancellation, in hand-free telephone systems, is detailed. Some control strategies are presented; in particular a novel double-talk detector based on a spectral dissimilarity measure is introduced ; also, a twin-filter structure which significantly enhances the echo rejection is derived.     

Optimum filter banks for signal decomposition and its applicationin adaptive echo cancellation

The application of multirate filter banks in echo cancellation is investigated. The multiresolution algorithm is used to decompose the received sampling sequence into a number of components, and then, an adaptive algorithm is applied to cancel the echo in the received signal. In this paper, the performance of this method is discussed, from which optimal conditions for echo cancellation are established for the design of wavelet packet multiresolution decomposition. An efficient algorithm for designing such a set of optimal discrete filter banks is developed. The cases of optimal in-band and adjacent-band adaptive filtering are examined. Experimental results showed that the use of optimally designed multiresolution filter banks coupled with in-band or adjacent-band adaptive filtering is much more effective than the employment of commonly used wavelet filter banks. Furthermore, the use of the adjacent-band adaptive filtering algorithm has superior performance compared with that of the in-band filtering     

Subband adaptive filtering with real-valued subband signals foracoustic echo cancellation

Adaptive filtering in subbands was originally proposed to overcome the limitations of conventional least-mean-square (LMS) algorithms. In general, subband adaptive filters offer computational savings, as well as faster convergence over the conventional LMS algorithm. However, improvements to current subband adaptive filters could be further enhanced by a more elegant choice of their design/structure. Classical subband adaptive filters employ DFT-based analysis and synthesis filter banks which results in subband signals that are complex-valued. The authors modify the structure of subband adaptive filters by using single-sideband (SSB) modulated analysis and synthesis filter banks, which result in subband signals that are real-valued. This simplifies the realisation of subband adaptive filters     

The Wheatstone bridge-based analog adaptive filter with application in echo cancellation

In this paper, a new analog adaptive filter is introduced with application in adaptive echo cancellation namely, the Wheatstone bridge-based analog adaptive filter (WAAF). It is proved the WAAF is a variable weight analog IIR filter. IIR filter weights vary with gate-source voltage control of a MOSFET transistor in triode region. The best balance point control of the WAAF is achieved using least mean square (LMS) algorithm. It is proved that analog LMS algorithm converges faster than digital LMS adaptive filter. The superiority of the proposed WAAF is observed in the designing process, computational cost, convergence speed and real time operation. Also, experimental results show ability of the proposed WAAF in the hybrid circuit of the telephone echo cancellation.     

基于DSP Builder的回波抵消器设计与实现

针对通信中的回波问题,基于自适应滤波的最小均方（LMS）算法,设计了一个自适应回波抵消器。基于FPGA芯片,在DSP Builder平台上,有效结合MATLAB/Simulink和Quartus Ⅱ设计工具,根据模块化设计思想实现了LMS算法自适应回波抵消器硬件电路设计。软件仿真和系统FPGA硬件实测结果表明,该设计方法使回波抵消器的FPGA硬件实现更加简便快捷。     

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.     

Per-tone echo cancellation for DMT-based systems

A new echo cancellation structure for discrete multitone systems is presented, where each used tone has its own per-tone echo canceller in addition to a per-tone equalizer, which provides an alternative to currently employed time domain and time/frequency domain approaches. The per-tone approach enables us to optimize the signal-to-noise ratio for each tone separately by solving a minimum mean-square error problem for each tone, with implicit so-called joint shortening. Complexity during data transmission is compared for time domain, time/frequency domain, and per-tone echo cancellation. Structures with reduced complexity are derived for an interpolated and a decimated rate setup. Finally, simulation results for an asymmetric digital subscriber line setting demonstrate improved performance over time domain (or time/frequency domain) echo cancellation.     

Cascaded power symmetric IIR filter banks and continuityconstrained adaptive algorithms for acoustic echo cancellation insubbands

Teleconferencing systems and hands-free mobile terminals use acoustic echo cancellation (AEC) for high-quality full-duplex speech communication. The problem of aliasing in subband AEC is addressed. Filter banks with implicit notch filtering are derived from cascaded power symmetric-infinite impulse response (CFS-IIR) filters. It is shown that adaptive filters used with these filter banks must be coupled via continuity constraints to reduce the aliasing in the residual echo. A continuity constrained NLMS algorithm is therefore proposed and evaluated     

一种新NLMS自适应滤波算法及其在多路回波消除中的应用

提出一种NLMS改进算法并对其收敛性进行了证明。该算法计算复杂度低于Sankaran(1997)所提出的带有正交改正因子的归一化算法(NLMS-OCF)和仿射投影算法(APA),并具有易于实现等特点。仿真结果表明,以单路语音信号作输入时,新算法具有比NLMS-OCF算法更好的收敛速度和精度,而在收敛速度和精度相当的情况下,新算法比APA算法所占用的CPU时间少。将新算法扩展成两路算法后,扩展算法仍然保持了这些特点,与Sankaran(1999)两路NLMS-OCF及Benesty(1996)所提多路仿射算法(APA-MC)相比,新算法更适合于应用到多路回波消除等实时性要求高的场合。1     

Data-driven echo cancellation for a multitone modulation system

The problem of echo cancellation in a multitone modulation (MTM) scheme is addressed. A general model for the near-end echo is derived and is used to identify candidate data-driven echo canceller (DDEC) structures. The stability, steady state performance, and associated system complexity of an adaptive DDEC based on the stochastic gradient approach is developed. It is further shown how the symmetry in the derived echo path model can be exploited to enable a reduction in canceller complexity, enhancing convergence speed without sacrificing final SNR. Simulation results are provided that confirm the analytical predictions     

Subarray design for adaptive interference cancellation

A method for designing near optimal, tapered subarrays for adaptive interference cancellation is proposed. The design method simultaneously produces a complete ordered set of fixed beam definitions, or nonadaptive weight vectors. The designer may choose to implement the first K of these if he or she wishes to have exactly K adaptive weights. In other words, the digital-adaptive processing is done in beam space, such that the beams are designed using the proposed method. To facilitate an RF implementation of the nonadaptive beamformer, each auxiliary beam uses only a designer-specified number of the elements in the aperture, thereby reducing the number of waveguide connections required. This design approach is fundamentally different from conventional subarray design approaches in that the new designs utilize cost functions related to interference cancellation.     

Proportionate NSAF algorithms with sparseness-measured for acoustic echo cancellation

In acoustic echo cancellation (AEC), the sparseness of impulse responses can vary over time or/and context. For such scenario, the proportionate normalized subband adaptive filter (PNSAF) and μ-law (MPNSAF) algorithms suffer from performance deterioration. To this end, we propose their sparseness-measured versions by incorporating the estimated sparseness into the PNSAF and MPNSAF algorithms, respectively, which can adapt to the sparseness variation of impulse responses. In addition, based on the energy conservation argument, we provide a unified formula to predict the steady-state mean-square performance of any PNSAF algorithm, which is also supported by simulations. Simulation results in AEC have shown that the proposed algorithms not only exhibit faster convergence rate than their competitors in sparse, quasi-sparse and dispersive environments, but also are robust to the variation in the sparseness of impulse responses.