自适应噪声抵消系统的算法讨论与DSP实现研究

阐述了自适应滤波技术的发展及应用，研究并给出实现自适应噪声抵消技术的几种常用算法对算法的性能进行了计算机仿真比较，给出了仿真结果，最后以语音信号为例，在仿真成熟的基础上，提出了用DSP实时实现自适应噪声抵消的具体方案。     

一种用于自适应噪声抵消的变步长LMS算法

为了提高LMS自适应滤波算法的性能,在分析已有变步长算法的基础上进行了一些改 进。改进算法用误差信号的自相关来调节步长以实现对不相关噪声的更好抑制,且采 用先固定后变化的方法控制步长,兼顾了暂态和稳态性能。利用改进算法进行了自适应噪声 抵消的仿真实验,结果表明,基于改进变步长LMS算法的自适应噪声抵消器 能有效抵制噪声干扰,对含噪信号具有良好的消噪能力。     

自适应算法在干扰抵消器应用中的比较研究

文中介绍了自适应滤波算法的原理和干扰抵消器工作原理，并将LMS算法、NLMS算法和变步长LMS算法分别应用在了干扰抵消器中进行了仿真。仿真的结果表明，三种自适应算法运用到了干扰抵消器中，都可以很好地滤除干扰，提取有用信号。其中运用了变步长LMS算法的干扰抵消器无论在收敛速度和滤波性能上，都要强于其他两种算法。     

基于MATLAB的自适应噪声抵消器的设计与实现

阐述了自适应噪声抵消（ANC）技术的基本原理,基于自适应滤波器的原理,设计了自适应噪声抵消器;在对自适应滤波器相关理论研究的基础上,重点研究了自适应噪声抵消器的核心——LMS自适应滤波算法。在MATLAB中的Simulink下,建立了自适应噪声抵消器的模型,并通过设置不同的参数进行仿真,结果表明系统能够有效地从噪声中恢复出原始信号。最后对系统进行了性能分析,给出了自适应噪声抵消系统在实际应用中选取参考信号的要求。     

基于LMS算法的自适应噪声抵消器的设计与实现

自适应噪声抵消(Adaptive Noise Canceller,ANC)技术是一种有效的降噪技术,阐述了基于自适应滤波器的噪声抵消的基本原理和设计方案以及在QuatusII软件上调用Modelsim对自适应噪声抵消器进行了仿真,对其相关性能指标进行测试,验证了该自适应滤波器的可实现性,并进行了相关的优化,提高了算法性...     

一种快速自适应算法在噪声抵消中的应用

研究了自适应横向滤波器的一种快速算法（FTF）及其在噪声抵消中的作用，对算法进行了推导，归纳了计算步骤，噪声抵消实验表明有良好的效果。     

一种水下有源噪声抵消系统的设计

潜艇的自噪声是影响潜艇被动声纳系统性能的重要因素。对接收信号中的潜艇自噪声进行有源抵消,从而可提高被动声纳的作用距离。该文设计了一个针对舰艇艏端被动声纳平台的本艇自噪声有源抵消系统,并设计了其试验系统方案。采用直接-并联型结构的多通道有源陷波器和滤波最小均方误差算法(FXLMS)自适应滤波算法,有效地抑制了潜艇自噪声中的线谱分量,提高了接收端的输入信噪比,提高了被动声纳作用距离。     

自适应回波抵消器的理论分析与计算机模拟

本文首先建立了自适应回波抵消器的数学模型。然后对自适应回波抵消器的调整算法、稳定性、收敛性和稳态回波抵消性能进行了较为详细的理论分析和计算机模拟。最后讨论了近端话声信号对自适应回波抵消器的影响及其检测问题。     

一种改进的自适应回波抵消器的设计与实现

回波是广泛存在于各种通信信道中的噪声干扰.传统的回波抵消器只能滤除缓变的、线性的回波干扰,对一些非线性且较复杂的信道产生的回波,滤波效果并不理想.本文通过比较融合两种经典的自适应算法,LMS算法和RLS算法各自的优点,提出了一种改进的自适应回波抵消器的结构,该回波抵消器已通过MATLAB仿真实现.从仿真的结果来看,该回波抵消器在对信道的兼容性,以及鲁棒性均优于传统回波抵消器.     

基于M估计变步长自适应仿射投影算法的稳健时延估计

该文提出了一种基于M估计变步长自适应仿射投影方法的稳健时延估计(TDE)算法。该算法将自适应仿射投影算法应用于时延估计,无须事先假定信号和噪声的统计特性,自适应调整自身参数;应用稳健M估计理论,抵消重尾噪声干扰。数值仿真表明,在高斯噪声、非高斯噪声甚至冲激噪声的干扰下,该文算法比高阶统计量法和最小均方自适应法有更强的稳健性和更高的估计精度。     

Finite word-length effects in recursive least squares algorithms with application to adaptive equalization

In this paper we provide a summary of recent and new results on finite word length effects in recursive least squares adaptive algorithms. We define the numerical accuracy and numerical stability of adaptive recursive least squares algorithms and show that these two properties are related to each other, but are not equivalent. The numerical stability of adaptive recursive least squares algorithms is analyzed theoretically and the numerical accuracy with finite word length is investigated by computer simulation. It is shown that the conventional recursive least squares algorithm gives poor numerical accuracy when a short word length is used. A new form of a recursive least squares lattice algorithm is presented which is more robust to round-off errors compared to the conventional form. Optimum scaling of recursive least squares algorithms for fixedpoint implementation is also considered.     

Adaptive minimum bit-error rate beamforming

An adaptive beamforming technique is proposed based on directly minimizing the bit-error rate (BER). It is demonstrated that this minimum BER (MBER) approach utilizes the antenna array elements more intelligently than the standard minimum mean square error (MMSE) approach. Consequently, MBER beamforming is capable of providing significant performance gains in terms of a reduced BER over MMSE beamforming. A block-data adaptive implementation of the MBER beamforming solution is developed based on the Parzen window estimate of probability density function. Furthermore, a sample-by-sample adaptive implementation is considered, and a stochastic gradient algorithm, referred to as the least bit error rate, is derived. The proposed adaptive MBER beamforming technique provides an extension to the existing work for adaptive MBER equalization and multiuser detection.     

A recursive least M-estimate algorithm for robust adaptive filtering in impulsive noise: fast algorithm and convergence performance analysis

This paper studies the problem of robust adaptive filtering in impulsive noise environment using a recursive least M-estimate algorithm (RLM). The RLM algorithm minimizes a robust M-estimator-based cost function instead of the conventional mean square error function (MSE). Previous work has showed that the RLM algorithm offers improved robustness to impulses over conventional recursive least squares (RLS) algorithm. In this paper, the mean and mean square convergence behaviors of the RLM algorithm under the contaminated Gaussian impulsive noise model is analyzed. A lattice structure-based fast RLM algorithm, called the Huber Prior Error Feedback-Least Squares Lattice (H-PEF-LSL) algorithm is derived. Part of the H-PEF-LSL algorithm was presented in ICASSP 2001. It has an order O(N) arithmetic complexity, where N is the length of the adaptive filter, and can be viewed as a fast implementation of the RLM algorithm based on the modified Huber M-estimate function and the conventional PEF-LSL adaptive filtering algorithm. Simulation results show that the transversal RLM and the H-PEF-LSL algorithms have better performance than the conventional RLS and other RLS-like robust adaptive algorithms tested when the desired and input signals are corrupted by impulsive noise. Furthermore, the theoretical and simulation results on the convergence behaviors agree very well with each other.     

基于MIMO信道估计误差模型的功率分配与自适应调制算法

该文分析了瑞利平坦衰落信道下,信道估计误差对采用迫零接收的MIMO系统性能的影响,提出了一种以系统有效吞吐量最大化为目标的功率分配与自适应调制算法。为了减少信道估计误差对实际系统性能的影响,该算法对发送端估计的信噪比进行修正,并以此作为功率分配和自适应调制的依据。在系统总功率受限的条件下,对发端多天线的功率分配结合了空域注水定理和比特分配,并尽量保证调制阶数高的数据符号所在天线的功率。仿真结果表明,该算法实现较简单,获得的系统有效吞吐量接近于最优值,适用于实际系统。     

Adaptive joint beamforming and B‐MMSE detection for CDMA signal reception under multipath interference

The combination of antenna array beamforming with multiuser detection can effectively improve the detection efficiency of a wireless system under multipath interference, especially in a fast‐fading channel. This paper studies the performance of an adaptive beamformer incorporated with a block‐wise minimum mean square error(B‐MMSE) detector, which works on a unique signal frame characterized by training sequence preamble and data blocks segmented by zero‐bits. Both beam‐former weights updating and B‐MMSE detection are carried out by either least mean square (LMS) or recursive least square (RLS) algorithm. The comparison of the two adaptive algorithms applied to both beamformer and B‐MMSE detector will be made in terms of convergence behaviour and estimation mean square error. Various multipath patterns are considered to test the receiver's responding rapidity to changing multipath interference. The performance of the adaptive B‐MMSE detector is also compared with that of non‐adaptive version (i.e. through direct matrix inversion). The final performance in error probability simulation reveals that the RLS/B‐MMSE scheme outperforms non‐adaptive B‐MMSE by 1–5 dB, depending on the multipath channel delay profiles of concern. The obtained results also suggest that adaptive beamformer should use RLS algorithm for its fast and robust convergence property; while the B‐MMSE filter can choose either LMS or RLS algorithm depending on antenna array size, multipath severity and implementation complexity. Copyright © 2004 John Wiley & Sons, Ltd.     

Adaptive minimum symbol-error-rate decision feedback equalization for multilevel pulse-amplitude modulation

The design of decision feedback equalizers (DFEs) is typically based on the minimum mean square error (MMSE) principle as this leads to effective adaptive implementation in the form of the least mean square algorithm. It is well-known, however, that in certain situations, the MMSE solution can be distinctly inferior to the optimal minimum symbol error rate (MSER) solution. We consider the MSER design for multilevel pulse-amplitude modulation. Block-data adaptive implementation of the theoretical MSER DFE solution is developed based on the Parzen window estimate of a probability density function. Furthermore, a sample-by-sample adaptive MSER algorithm, called the least symbol error rate (LSER), is derived for adaptive equalization applications. The proposed LSER algorithm has a complexity that increases linearly with the equalizer length. Computer simulation is employed to evaluate the proposed alternative MSER design for equalization application with multilevel signaling schemes.     

Coded asynchronous CDMA and its efficient detection

In this paper, receiver design and performance analysis for coded asynchronous code-division multiple access (CDMA) systems is considered. The receiver front-end consists of the near-far resistant multiuser detector known as the projection receiver (PR). The PR performs multiple-access interference resolution and is followed by error-control decoding. The output of the projection receiver yields the appropriate metric (i.e., soft information) for decoding of the coded sequences. An expression for the metric is derived that allows the use of a standard sequence decoder (e.g., Viterbi algorithm, M-algorithm) for the error-control code. It is then shown that the metric computer has an elegant adaptive implementation based on an extension of the familiar recursive least squares (RLS) algorithm. The adaptive PR operates on a single sample per chip and achieves a performance virtually identical to the algebraic PR, but with significantly less complexity. The receiver performance is studied for CDMA systems with fixed and random spreading sequences, and theoretical performance degradations with regard to the single-user bound are derived. The near-far resistance of the PR is also proven, and demonstrated by simulation     

Low-complexity adaptive decision-feedback equalization of MIMO channels

A new adaptive MIMO channel equalizer is proposed based on adaptive generalized decision-feedback equalization and ordered-successive interference cancellation. The proposed equalizer comprises equal-length subequalizers, enabling any adaptive filtering algorithm to be employed for coefficient updates. A recently proposed computationally efficient recursive least squares algorithm based on dichotomous coordinate descents is utilized to solve the normal equations associated with the adaptation of the new equalizer. Convergence of the proposed algorithm is examined analytically and simulations show that the proposed equalizer is superior to the previously proposed adaptive MIMO channel equalizers by providing both enhanced bit error rate performance and reduced computational complexity. Furthermore, the proposed algorithm exhibits stable numerical behavior and can deliver a trade-off between performance and complexity.     

Adaptive Minimum Symbol Error Rate Beamforming Assisted Detection for Quadrature Amplitude Modulation

We consider beamforming assisted detection for multiple antenna aided multiuser systems that employ the bandwidth efficient quadrature amplitude modulation scheme. A minimum symbol error rate (MSER) design is proposed for the beamforming assisted receiver, and it is shown that this MSER design provides significant performance enhancement, in terms of achievable symbol error rate, over the standard minimum mean square error (MMSE) design. A sample-by-sample adaptive algorithm, referred to as the least symbol error rate, is derived for adaptive implementation of the MSER beamforming solution. The proposed adaptive MSER scheme is evaluated in simulation using Rayleigh fading channels, in comparison with the adaptive MMSE benchmarker.     

Adaptive linearly constrained inverse QRD-RLS beamforming algorithm for moving jammers suppression

A general, linearly constrained (LC) recursive least squares (RLS) array-beamforming algorithm, based on an inverse QR decomposition, is developed for suppressing moving jammers efficiently. In fact, by using the inverse QR decomposition-recursive least squares (QRD-RLS) algorithm approach, the least-squares (LS) weight vector can be computed without back substitution and is suitable for implementation using a systolic array to achieve fast convergence and good numerical properties. The merits of this new constrained algorithm are verified by evaluating the performance, in terms of the learning curve, to investigate the convergence property and numerical efficiency, and the output signal-to-interference-and-noise ratio. We show that our proposed algorithm outperforms the conventional linearly constrained LMS (LCLMS) algorithm, and the one using the fast linear constrained RLS algorithm and its modified version.