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The presence of non-Gaussian impulsive noise in wireless system can degrade the performance of existing equalizers and signal detectors. In this paper, the problem of blind source separation and equalization for MIMO systems in heavy-tailed impulsive noise is studied. A generalized multiuser constant modulus cost function by employing the fractional lower-order statistic of the equalizer input signal is proposed. The associated adaptive blind equalization algorithm based on a stochastic gradient descent method is defined as fractional lower-order multi-user constant modulus algorithm (FLOS MU CMA). Computer simulations are presented to illustrate the performance of the new algorithm. 相似文献
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以常数模和判决引导准则设计的双模式盲均衡算法可显著提高均衡性能,目前已有双模式盲均衡算法均需设置切换参数且切换参数选择和设定缺乏理论依据.为解决双模式盲均衡算法中切换参数难以确定的问题,提出来一种组合代价函数的双模式盲均衡新算法.利用常数模和判决引导准则通过加权设计代价函数,在盲均衡器更新过程中自适应调节权值实现算法由常数模算法向判决引导算法的切换,避免了在双模式算法中设计切换参数,提高了算法的泛化性能.为克服常数模算法相位盲的缺点,在虚实分开改进的常数模算法基础上优化组合代价函数以及盲均衡器更新算法的设计,进一步提高了算法收敛性能.仿真结果证明,组合代价函数双模式盲均衡新算法可充分发挥常数模算法和判决引导算法的优点,具有更快的收敛速度和更小的稳态剩余误差. 相似文献
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针对恒模算法(constant modulus algorithm, CMA)在脉冲噪声环境下性能退化的问题,本文基于最大相关熵准则(maximum correntropy criterion, MCC)对恒模算法中基于最小均方误差(mean square error, MSE)准则的代价函数进行修正,推导出适用于脉冲噪声环境的基于MCC准则的恒模盲均衡算法(MCC_CMA)。该算法利用通信信号的恒模特性,首先得到发送信号与均衡器输出信号模值的误差信号,再通过使模值误差信号的相关熵最大来获得其迭代误差调节项,避免了传统高阶统计量算法在脉冲噪声环境下性能退化的问题。对高斯噪声以及α-稳定分布和混合高斯分布两种脉冲噪声环境下的信道均衡问题的仿真实验表明,相对于经典的自适应恒模盲均衡算法,MCC_CMA算法不依赖噪声的先验知识就能获得较快的收敛速度、较低的剩余码间干扰和误码率,并且在不同脉冲强度的脉冲噪声环境下都能够得到较好的均衡结果,表明MCC_CMA算法具有很好的鲁棒性。 相似文献
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There are serious intersymbol interference (ISI) and signal attenuation in wireless ultraviolet communication system.Aiming at this problem,an improved constant modulus fractionally spaced equalizer (CMA-FSE) based on signal-to-noise (SNR) estimation was proposed.The algorithm combined the fractionally spaced equalizer (FSE) and constant modulus algorithm (CMA) for blind equalization of wireless ultraviolet channels.The input SNR was measured by the mean square value of the received signal,and it was used to determine the best iterative step to ensure the convergence of the equalization algorithm.Simulation results show that the improved CMA-FSE algorithm can converge rapidly under various SNR,and it can effectively suppress ISI and improve the BER performance of the system.Compared with the existing algorithms,the improved algorithm is more useful in channel tracking and noise suppression. 相似文献
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该文提出一种基于预处理递归最小二乘恒模算法(PP-RLSCMA)的多径异步CDMA系统盲自适应接收技术。首先对接收信号进行自适应预处理,并分析了预处理器的复杂性和稳定性。预处理的目的是通过对干扰和噪声的部分抑制以提高恒模接收的性能,所提出的预处理方法只与多径信道的最大长度有关。鉴于统计恒模算法收敛速度慢的缺点,提出一种快速递归最小二乘恒模算法的盲自适应接收。仿真表明,该文算法的误码率及收敛性能比LCMMV,LCCMA好。 相似文献
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A hybrid adaptive blind equalization algorithm for QAM signals in wireless communications 总被引:8,自引:0,他引:8
Lin He Amin M.G. Reed C. Jr. Malkemes R.C. 《Signal Processing, IEEE Transactions on》2004,52(7):2058-2069
A hybrid adaptive channel equalization technique for quadrature amplitude modulation (QAM) signals is proposed. The proposed algorithm, which is referred to as the modified constant modulus algorithm (MCMA), minimizes an error cost function that includes both amplitude and phase of the equalizer output. In addition to the amplitude-dependent term that is provided by the conventional constant modulus algorithm (CMA), the cost function includes an additive signal constellation matched error (CME) term. This term can be designed to satisfy a set of desirable properties. The MCMA is compared with the CMA for blind equalization. The performance is measured for wireless channels using both transient and steady-state behavior of the mean square error (MSE). It is shown that MCMA is superior and more robust in low signal-to-noise ratio (SNR) environments. Simulation results demonstrate that using MCMA improves adaptive channel equalization by increasing the convergence rate and decreasing the steady-state mean square error. 相似文献
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针对脉冲噪声下恒模算法(Constant Modulus Algorithm,CMA)失败的问题,通过分析脉冲噪声的影响,提出了一种基于最小均方(Least Mean Square,LMS)准则的对数型恒模算法(Logarithmic-type CMA,LT-CMA)。LT-CMA利用对数函数的非线性变换特性自适应地抑制强脉冲噪声对误差函数的影响,并且利用l2-范数进行信号归一化处理以增强算法的稳健性。仿真结果表明,所提出的LT-CMA可以适应于高斯噪声环境和脉冲噪声环境;与经典自适应均衡算法相比,在收敛速度和稳健性两方面上,所提出的LT-CMA都有显著的提升。 相似文献
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Zou Y. Chan S.C. Ng T.S. 《Vision, Image and Signal Processing, IEE Proceedings -》2001,148(4):289-294
An M-estimate adaptive filter for robust adaptive filtering in impulse noise is proposed. Instead of using the conventional least-square cost function, a new cost function based on an M-estimator is used to suppress the effect of impulse noise on the filter weights. The resulting optimal weight vector is governed by an M-estimate normal equation. A recursive least M-estimate (RLM) adaptive algorithm and a robust threshold estimation method are derived for solving this equation. The mean convergence performance of the proposed algorithm is also analysed using the modified Huber (1981) function (a simple but good approximation to the Hampel's three-parts-redescending M-estimate function) and the contaminated Gaussian noise model. Simulation results show that the proposed RLM algorithm has better performance than other recursive least squares (RLS) like algorithms under either a contaminated Gaussian or alpha-stable noise environment. The initial convergence, steady-state error, robustness to system change and computational complexity are also found to be comparable to the conventional RLS algorithm under Gaussian noise alone 相似文献
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The paper addresses the problem of blind equalization of constant modulus signals which are degraded by frequency selective multipath propagation and additive white noise. An adaptive observer is used to update the weights of an FIR equalizer in order to restore the signal's constant modulus property. The observer gain is selected using fake algebraic Riccati methods in order to guarantee local stability. The performance of this method is compared to the constant modulus algorithm for simulated FM-FDM signals and exhibits significantly better convergence properties, particularly for heavy-tailed noise 相似文献
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Space-time blind equalisation in impulsive noise 总被引:1,自引:0,他引:1
S. Li T.Sh. Qiu Sh.F. Zhang 《Signal Processing, IET》2009,3(6):445-458
The presence of non-Gaussian impulsive noise in wireless system can degrade the performance of existing equalisers and signal detectors. The problem of blind source separation and equalisation for multipleinput/ multiple-output (MIMO) channels under heavy-tailed impulsive noise environment is studied. A generalised multi-user constant modulus (CM) cost function is proposed by employing the fractional lower order CM property of the equaliser input signals as well as the fractional lower order cross-correlations between them. The associated adaptive blind equalisation algorithm based on a stochastic gradient descent method is defined as fractional lower order multi-user constant modulus algorithm (FMU_CMA), which is able to mitigate impulsive channel noise while recovering all input signals simultaneously. The steady-state meansquare error (MSE) performance of the FMU_CMA is studied in a noise-free environment; the approximate expression is derived based on the energy-preserving relation and the Taylor series expansion. Simulation studies are undertaken to support the analysis with CM and non-CM signal. 相似文献
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Shing-Chow Chan Yue-Xian Zou 《Signal Processing, IEEE Transactions on》2004,52(4):975-991
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. 相似文献
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低频通信中脉冲型噪声会严重降低通信性能.针对脉冲型噪声的抑制问题,本文提出高斯拖尾零记忆非线性(Gaussian-tailed Zero Memory Nonlinearity,GZMNL)函数的最优化设计方法.GZMNL函数含有两个参数,分别控制其线性范围和拖尾程度,故适用于多种噪声分布.本文提出GZMNL设计以效能最大化为优化目标,采用自适应搜索算法来寻找GZMNL参数的最佳值.然后讨论了GZMNL在SαS(Symmetric α-Stable,SαS)噪声分布下的快速设计方法,以及在未知噪声分布时的稳健设计方法.最后,仿真SαS噪声和实测大气噪声数据的处理结果表明:本文设计方法在检测性能上能够接近最优非线性,且能够有效抑制未知分布的噪声. 相似文献
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在无线通信信道中,码间干扰严重影响了通信的质量和可靠性。传统的自适应均衡算法需要训练序列降低了传输效率,恒模算法(CMA)可以很好的克服了这个问题。针对CMA算法收敛速度较慢和无法纠正相位误差的缺点,提出一种新的步长迭代方法的改进型恒模算法(NSMCMA)。蒙特卡罗仿真表明,提出的算法,相比传统CMA算法,不仅可以纠正信道的相位偏转,而且具有更好的均衡效果和收敛性能。 相似文献
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为了提高脉冲噪声下盲均衡器的性能,该文提出一种基于概率密度函数匹配与分数低阶矩的并行盲均衡算法。首先采用概率密度函数匹配的思想进行盲均衡,充分利用其收敛速度快的优势。为了解决此均衡过程中引起的相位信息损失以及抑制脉冲噪声能力差的问题,又以并行的方式结合判决信号的分数低阶矩,并以此作为代价函数来共同更新盲均衡器的权向量,进一步提高了算法在脉冲噪声下的收敛速度与收敛精度。仿真实验表明,所提算法在有效解决相位旋转问题的同时较好地抑制了脉冲噪声,此外还具有较快的收敛速度和较小的稳态误差,稳健性较强。 相似文献