Adaptive reduced-rank interference suppression based on themultistage Wiener filter

A class of adaptive reduced-rank interference suppression algorithms is presented based on the multistage Wiener filter (MSWF). The performance is examined in the context of direct-sequence (DS) code division multiple access (CDMA). Unlike the principal components method for reduced-rank filtering, the algorithms presented can achieve near full-rank performance with a filter rank much less than the dimension of the signal subspace. We present batch and recursive algorithms for estimating the filter parameters, which do not require an eigen-decomposition. The algorithm performance in a heavily loaded DS-CDMA system is characterized via computer simulation. The results show that the reduced-rank algorithms require significantly fewer training samples than other reduced- and full-rank algorithms     

Fast orthogonalization networks

A numerically efficient and stable algorithm is developed to adaptively filter multiple input channels into desired multiple output channels. The algorithm is a type of adaptive lattice filter that employs a fast orthogonalization network (FON) algorithm for numerical efficiency. Past researchers have concentrated on developing efficient lattice algorithms to process stationary input channels; i.e., the input covariance matrix is Toeplitz in form. The algorithm developed herein is designed to adaptively filter nonstationary input channels. Various implementations of the FON algorithm are given.     

Two algorithms for adaptive retrieval of slowly time-varyingmultiple cisoids in noise

Two algorithms for tracking parameters of slowly varying multiple complex sine waves (cisoids) in noise (the multiple frequency tracker and the adaptive notch filter) are described. For high signal-to-noise ratio (SNR), the properties of the algorithms (i.e., stability, noise rejection, and tracking speed) are studied analytically using a linear filter approximation technique. The tradeoff between noise rejection and tracking error for both algorithms is shown to be similar. Different choices of the design variables are discussed, namely (i) minimal mean-square estimation error for random walk modeled frequency variations and (ii) minimal stationary estimation variance subject to a given tracking delay     

Noncoherent MMSE interference suppression for DS-CDMA

A novel robust noncoherent receiver for minimum mean-squared error (MMSE) interference suppression for direct-sequence code-division multiple access (DS-CDMA) is proposed. The receiver consists of a linear MMSE filter and a decision-feedback differential detector (DF-DD). The performance of the proposed scheme is investigated analytically and by computer simulations. It is shown that the loss compared to coherent MMSE interference suppression is limited and can be made arbitrarily small by increasing the observation window used for calculation of the reference symbol of the DF-DD. Hence, the regarded noncoherent receiver is near-far resistant. For adjustment of the MMSE filter coefficients three noncoherent adaptive algorithms are proposed. In contrast to coherent adaptive algorithms, these noncoherent algorithms have the important advantage that they also converge if the channel phase is time-variant     

一种应用于限制零极点位置复数陷波器的迭代算法

基于最小均方误差准则(MMSE),本文推导出了一种修改限制零极点位置的一阶复数陷波器权值迭代算法,并进而提出了一种新的可应用于矩阵型高阶陷波器的自适应权值修改算法,该高阶陷波器由一阶陷波器作为陷波单元构成。该迭代算法直接修改陷波器权值的指数,因而在算法迭代过程中能够将高阶复数陷波器的极点始终限制在单位圆内,从而保证了陷波器的稳定工作。仿真结果表明,采用该算法的一阶和高阶复数陷波器工作稳定,对输入陷波器的宽带信号损伤小,且能快速跟踪和有效抑制其中的强单/多频信号。     

Performance evaluation of LMS-based adaptive suppression schemes in asynchronous CDMA

The objective of this paper is to evaluate the bit-error-rate performance of various adaptive structures in combating multi-user interference in an asynchronous code division multiple access (CDMA) system. In particular, two adaptive schemes, known as the N-tap filter and D-tap cyclical shifted bank filter, are considered. The least mean square (LMS) and predictive LMS (PLMS) algorithms are employed for the adaptation of tap weights. An analytical expression is developed for the numerical evaluation of the bit error probability. In addition, the bit error rate performances of the adaptive schemes are compared with those of the matched filter receiver. Results attest to the pratical usefulness of the LMS-based adaptive suppression schemes in combating multi-user interference in an asynchronous CDMA system.     

Partial update and sparse adaptive filters

There has been increasing research interest in developing adaptive filters with partial update (PU) and adaptive filters for sparse impulse responses. On the basis of maximum a posteriori (MAP) estimation, new adaptive filters are developed by determining the update when a new set of training data is received. The MAP estimation formulation permits the study of a number of different prior distributions which naturally incorporate the sparse property of the filter coefficients. First, the Gaussian prior is studied, and a new adaptive filter with PU is proposed. A theoretical basis for an existing PU adaptive filter is also studied. Then new adaptive filters that directly exploit the sparsity of the filter are developed by using the scale mixture Gaussian distribution as the prior. Two new algorithms based on the Student's-t and power-exponential distributions are presented. The minorisation-maximisation algorithm is employed as an optimisation tool. Simulation results show that the learning performance of the proposed algorithms is better than or similar to that of some recently published algorithms     

Data-aided and blind stochastic gradient algorithms for widely linear MMSE MAI suppression for DS-CDMA

In this paper, three novel stochastic gradient algorithms for adjustment of the widely linear (WL) minimum mean-squared error (MMSE) filter for multiple access interference (MAI) suppression for direct-sequence code-division multiple access (DS-CDMA) are introduced and analyzed. In particular, we derive a data-aided WL least-mean-square (LMS) algorithm, a blind WL minimum-output-energy (MOE) algorithm, and a WL blind LMS (BLMS) algorithm. We give analytical expressions for the steady-state signal-to-interference-plus-noise ratios (SINRs) of the proposed WL algorithms, and we also investigate their speed of convergence. Wherever possible, comparisons with the corresponding linear adaptive algorithms are made. Both analytical considerations and simulations show, in good agreement, the superiority of the novel WL adaptive algorithms. Nevertheless, all proposed WL algorithms require a slightly lower computational complexity than their linear counterparts.     

最大互相关熵多凸组合自适应滤波算法

基于最大互相关熵准则(MCC)的自适应滤波算法在非高斯噪声环境下具有强鲁棒性,得到了广泛应用。然而,传统MCC滤波算法在选择参数时依然受到收敛速度与稳态精度之间固有矛盾的困扰。为解决这一问题,该文提出一类多凸组合MCC算法,能够充分发挥不同参数组合下滤波算法的性能优势,从而获得更好的信道跟踪能力。理论分析得出了所提算法的均值收敛条件和稳态均方误差,同时,仿真实验表明所提算法在对抗高斯和非高斯噪声时均具有收敛快、稳态精度高的特点。     

Line search algorithms for adaptive filtering

Line search algorithms for adaptive filtering that choose the convergence parameter so that the updated filter vector minimizes the sum of squared errors on a linear manifold are described. A shift invariant property of the sample covariance matrix is exploited to produce an adaptive filter stochastic line search algorithm for exponentially weighted adaptive equalization requiring 3N+5 multiplications and divisions per iteration. This algorithm is found to have better numerical stability than fast transversal filter algorithms for an application requiring steady-state tracking capability similar to that of least-mean square (LMS) algorithms. The algorithm is shown to have faster initial convergence than the LMS algorithm and a well-known variable step size algorithm having similar computational complexity in an adaptive equalization experiment     

虚拟多参考输入自适应同址干扰抵消算法

针对同一空间内相邻发射机对接收机产生的同址干扰,将接收信号过采样后虚拟出多路参考信号并与两级自适应滤波器相结合,构成了一种虚拟多参考输入自适应同址干扰抵消算法。通过在接收纯干扰信号阶段调整第一阶滤波器的权系数,接收信号中包含有用信号时调整第二阶滤波器的系数,实现消除同址干扰恢复有用信号的功能。仿真结果表明,所提同址干扰抵消算法与传统算法相比,在简化了耦合装置的同时,也具有更好的同址干扰抑制效果。     

Adaptive blind receivers for MC‐CDMA communication systems

In this paper, we propose three adaptive blind algorithms for multiuser multicarrier code division multiple‐access systems in multipath fading channels. The proposed adaptive blind receivers are based on the property of the discreteness of the input data symbol and are updated in every symbol interval. We also use the concept that the variance of the output signal approaches to the variance of the desired signal to get the cost function. The three proposed receiver structures are the traditional finite impulse response (FIR) structure, the despreading (DES) filter structure and the generalized sidelobe canceller (GSC) structure. The advantage of the FIR filter is that the length of the filter weights does not have to be the same length as the spreading code. For the DES filter, the combination of the adaptive weight and the despreading code has the simplest structure than the other two proposed receiver structures. The constrained GSC filter is superior to the other two proposed receiver structures in the environments dominated by multiple‐access interference. By this constraint, the blind GSC filter can guarantee to converge to the desired solution. Simulation results are given to show the effectiveness and comparison of the proposed adaptive blind receivers. Copyright © 2012 John Wiley & Sons, Ltd.     

Adaptive algorithms for joint time delay estimation and IIRfiltering

A new class of gradient-based algorithms for joint adaptive time delay estimation and IIR filtering for the recursive identification of systems with long pure delays is introduced. The algorithms update an adaptive delay estimate and the coefficients of an IIR filter using familiar gradient-descent methods. In addition, interpolation of the input sequence is used to obtain delays that are not constrained to integer numbers of samples. Three algorithms using a direct form filter parametrization and one using a normalized lattice filter are derived, and computer simulations are used to demonstrate their convergence and tracking properties     

Multiplication-free adaptive digital filters

The authors update delta modulation digital filter weights using the LMS (least-mean-squares) and the SIGN algorithms to realize an adaptive digital filter without multiplication operations. It is shown that using the SIGN algorithm results in an adaptive filter that can be implemented using the simple up/down counting operations. Learning curves demonstrating convergence properties of the algorithms for a system identification problem are presented     

Robust adaptive estimator for filtering noise in images

Provides three new methods for storing images corrupted by additive noise. One is the adaptive mean median filter for preserving the details of images when restored from additive Gaussian noise. Another is the minimum-maximum method for moving outlier noise. The third method, the robust adaptive mean p-median filter, is based on a combination of the previous two methods. In the past, proposed restoration methods have generally proven to be inadequate for both detail preservation and noise suppression, but the new adaptive mean p-median filter is shown to be good at both of these tasks, while the robust adaptive mean p-median filter can give good performance even in the presence of outliers. Degraded images are processed by the proposed algorithms, with the results compared with a selection of other median-based algorithms that have been proposed in the literature.     

Interference rejection using the time-dependent constant modulusalgorithm (CMA) and the hybrid CMA/spectral correlation discriminator

Two new blind adaptive filtering algorithms for interference rejection using time-dependent filtering structures are presented. The time-dependent structure allows the adaptive filter to outperform the conventional adaptive filter implemented with a time-independent structure for filtering of cyclostationary communication signals. At the same time, the blind adaption algorithms allow the filters to operate without the use of an external training signal. The first algorithm applies the CMA to an unconstrained time-dependent filtering structure. The second algorithm applies the CMA to a spectral correlation discriminator, which is constrained to select signals with unique spectral correlation characteristics. Using computer simulations, it is shown that the blind time-dependent filtering algorithms can provide mean-square errors (MSEs) and bit error rates (BERs) that are significantly lower than the MSEs and BERs provided using conventional time-independent adaptive filters. It is also shown that these processors can outperform the nonblind training-sequence directed time-independent adaptive filter     

New forms of Levinson and Schur algorithms

The Levinson and Schur solutions to the adaptive filtering and parameter estimation problem of recursive least squares processing are described. Unnormalized versions of a newly developed Schur RLS adaptive filter are presented. A systolic array of the Schur RL adaptive filter is devised and its performance is illustrated with a typical example. The classical Levinson and Schur algorithms drop out as special cases of the more general Levinson and Schur RLS adaptive filtering algorithms. The recently introduced split Levinson and Schur algorithms, which are obtained by exploiting the symmetry in the Toeplitz-structured extended normal equations, are reviewed     

噪声点位置已知的自适应滤波算法比较研究

高效滤除图像中椒盐噪声的方法大多采用先检测被污染图像中椒盐噪声的位置,再有针对性地对椒盐噪声进行处理的方法。噪声检测算法精度均较高,滤波质量与后续采用的自适应开关滤波算法息息相关。文中在图像椒盐噪声位置已知的情况下,比较研究了应用较为广泛的3种自适应开关滤波算法的去噪性能。     

Performance of adaptive linear interference suppression in thepresence of dynamic fading

Adaptive linear interference suppression for direct-sequence (DS) code-division multiple access (CDMA) is studied in the presence of time- and frequency-selective fading. Interference suppression is achieved with an adaptive digital filter which spans a single symbol interval. Both decision-directed and blind adaptive algorithms, which do not require a training sequence, are considered. Modifications to least squares adaptive algorithms are presented which are compatible with differential coding and detection. For frequency-selective fading, adaptive algorithms are presented based upon different assumptions concerning knowledge of the desired user's channel. Specifically, the cases considered are as follows: (1) perfect knowledge of the desired channel; (2) knowledge of only the relative path delays; and (3) knowledge of only one delay corresponding to the strongest path. Computer simulation results are presented which compare the performance of these algorithms with the analogous RAKE receivers. These results show that for case (3), even slow fading can cause a significant degradation in performance. Effective use of channel parameters in the adaptive algorithm reduces the sensitivity to fade rate, although moderate to fast fading can significantly compromise the associated performance gain relative to the RAKE receiver     

Multiaccess Interference Suppression in Orthogonal Space–Time Block Coded MIMO Systems by Adaptive Projected Subgradient Method

This paper introduces adaptive filters that are effective to suppress multiple access interference (MAI) in orthogonal space-time block coded/ multiple-input multiple-output (OSTBC-MIMO) systems. We define an optimal linear filter that minimizes the mean-square error between the filter output and a scaled version of the desired output under a constraint defined by the available channel state information (CSI). The adaptive filters refine a given estimate of the optimal filter by suppressing a sequence of closed convex functions with the adaptive projected subgradient method (APSM) at each iteration. To provide robustness against imperfect CSI, the adaptive filters use not only the available CSI but also estimates of previously transmitted symbols, which usually belong to a small finite set in digital communication systems. The resulting algorithms employ computationally efficient projections onto hyperplanes or hyperslabs and do not require any matrix inversion. An efficient recursive scheme based on such an algorithm is also presented. Convergence analysis and simulation results show the excellent performance of the proposed schemes.