基于概率软切换的两级双模盲均衡器

文中提出一种基于概率软切换的两级双模盲均衡器。它实时统计两级盲均衡器输出硬判决值相同的概率,并利用它切换盲均衡算法。该均衡器结合了级联两级均衡结构和双模算法的优点。仿真表明,它能够纠正相位偏移,相对于波特间隔（BSE）的并发常模＋判决导引（CMA＋DD）盲均衡器,以非常小的计算复杂度代价,获得稳态均方误差（MSE）性能和误比特率（BER）性能的较大提高。     

一种常数模与判决导引相结合的盲均衡算法研究

虽然判决导引最小均方误差算法（DD－LMS）剩余误差小，但是，在信道眼图闭合的情况下，该算法无法收敛，即不具备冷启动能力。本文根据信噪比确定了判决圆边界，对均衡器的输出进行判决，将常数模算法（CMA）和DD算法有机地结合起来，计算机仿真表明：算法性能稳健，具有冷启动能力和重新启动能力，计算量增加也很小。     

一种新的混合盲均衡算法的研究

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。恒模算法（CMA）可以很好的克服码间干扰。针对CMA算法收敛速度较慢和无法纠正相位误差的缺点,提出将改进型CMA算法和改进型判决引导（DD）算法结合起来的混合盲均衡算法。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。     

无人机数据链信道均衡技术仿真研究

信道均衡技术是无线通信中解决码间干扰的关键技术.选取LMS,RLS和CMA常用的均衡算法以及信道均衡器的结构作为研究对象,通过对三种均衡算法的收敛性能的仿真分析,以及结合无人机信道模型对常用的两种均衡结构的误码性能进行的仿真,所得结果对于后期基于FPGA实现高速的信道均衡器时算法和结构的选择具有参考的价值.     

无线通信中的恒模类盲均衡算法研究

在无线通信系统中，码间干扰（ISI）是影响通信质量的重要因素。盲均衡技术不需要发送导频序列便能自适应调节均衡器抽头系数，能够有效去除ISI。文中介绍了盲均衡技术原理，重点研究了恒模类盲均衡算法，通过对恒模算法（CMA）和改进的CMA算法（包括MMA算法和双模式盲均衡算法）的迭代公式分析，得出了恒模类盲均衡算法的性能。计算机仿真表明恒模类盲均衡算法在无线通信中具有良好的均衡性能。     

一种用于数字QAM解调芯片中的盲均衡器实现

设计了一种用于数字QAM解调芯片中的自适应盲均衡器。该均衡器采用常模算法（CMA）和判决引导最小均方算法（DD-LMS）,结合判决反馈结构（DFE）,即采用前向滤波和反馈滤波两级滤波器组,该方案提高了信道的自适应性能和降低了均衡器的阶数。通过对算法的简化和电路结构的优化,减少了硬件资源,降低了电路的面积和功耗。     

高性能数字电视QAM均衡器的VLSI结构设计

本文设计了一种适用于高清晰数字电视（HDTV）接收芯片的全数字正交幅度调制器（QAM）的均衡器。该均衡器由前馈滤波器、误差判别电路和系数更新电路以及后馈滤波器构成。该均衡器采用了常模算法（CMA）和判决导引最小均方算法（DD-LMS）相结合的算法。重点给出了均衡器的VLSI实现、两种算法间切换的依据、步长的选择以及抽头系数的确定。同时在电路上采用了逻辑简化、重编码、电路时分复用等简化和优化方法来实现性能、面积和功耗的折衷。     

一种用于数字QAM接收机的盲均衡器实现

提出了一种适用于数字QAM接收机的自适应盲均衡器实现方案。该均衡器采用多模算法(MMA)和最小均方算法(LMS)，称为MMA—LMS算法结合判决反馈结构(DFE)，即采用前向滤波器和反馈滤波器两级滤波器组实现，提高了信道的适应性能和降低均衡器的阶数。仿真结果表明，该均衡器比一般采用恒模算法(CMA)的横式均衡器有更好的性能，更易于硬件实现。     

双模式神经网络盲均衡算法研究

文中以前馈神经网络作为盲均衡器,根据CMA盲均衡算法及决策指向性算法(DD)提出了两种神经网络学习目标函数,并在对两种目标函数下神经网络盲均衡算法性能分析的基础上,给出了依据移动窗剩余误差理论确定切换门限的方法,提出了双模式神经网络盲均衡算法,并以短数据样本重用确定网络的初始权重.仿真表明文中提出的双模式神经网络盲均衡算法能够克服在单一目标函数下神经网络盲均衡算法的缺陷,且收敛速度快,有效的提高了均衡性能.     

一种应用于QAM信号的新型高速均衡器

提出了一种基于新型算法SGLMS-CMA的高速QAM均衡器.SGLMS-CMA算法在stop-and-go原理指导下结合了经典CMA算法和DD-LMS算法.MATLAB仿真表明,与经典CMA算法相比,新型算法具有收敛速度快5倍,剩余MSE改善3～5dB,运算复杂度减少了82%,可纠正残留相偏的优点.综合结果表明,采用SGLMS-CMA+DD-LMS的新型均衡器与CMA+DD-LMS均衡器相比,系统中均衡器模块的硬件开销只增加5%.最后使用SMIC 0.18μm工艺库对新型均衡器进行综合,并且嵌入到QAM解调芯片中进行流片,最终测试结果表明新型均衡器性能优越.     

Convergence analysis of the stop-and-go blind equalizationalgorithm

Unlike traditional trained channel equalizers, not much work has been done to theoretically characterize the convergence properties of blind channel equalizers due to their inherent nonlinearity. It is only recently that convergence properties of some well-known algorithms such as the generalised Sato algorithm (GSA) and the constant modulus algorithm (CMA) have been analytically derived. In this paper, the convergence properties of the stop-and-go algorithm proposed by Picchi and Prati (1987) are analyzed. The derived mean squared error and the coefficient trajectories are compared with simulation results to verify the validity of the analytical results     

一种改进的波束形成算法

论文分析研究了最陡下降恒模算法（SDCMA）在波束形成应用中收敛稳定性好和最小二乘恒模算法（LSCMA）收敛速度快的特点,将两种算法以新的方式相结合,吸收二者的优点,提出了一种基于预解扩判决反馈盲波束形成组合算法（SD—LSCMA）。通过和传统算法在相同环境下进行MATLAB仿真比较,结果表明,文中提出的算法具有更好的抗强多址干扰性能。     

Low complexity concurrent constant modulus algorithm and soft decision directed scheme for blind equalisation

The recently introduced concurrent constant modulus algorithm (CMA) and decision-directed (DD) scheme provides a state-of-the-art low-complexity blind equalisation technique for high-order quadrature amplitude modulation (QAM) channels. At a small cost of slightly more than doubling the complexity of the standard CMA blind equaliser, this concurrent CMA and DD blind equaliser achieves a dramatic improvement in equalisation performance over the CMA. In the paper, a new blind equalisation scheme is proposed based on concurrent CMA and a novel soft decision-directed (SDD) adaptation. The proposed concurrent CMA and SDD blind equaliser has simpler computational requirements than the concurrent CMA and DD algorithm. Extensive simulation shows that it has the same steady-state equalisation performance as the concurrent CMA and DD algorithm and a faster convergence speed over the latter scheme     

基于组合代价函数的双模式盲均衡新算法

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.     

一种改进的QAM信号的恒模算法：MCADAMA

提出了一种适用于QAM系统的改进的双模式算法MCADAMA（modified CMA-assisted decision adjusted modulus algorithm）。通过研究Axford提出的CADAMA双模式算法,受到MCMA算法的启发,结合恒模算法的特性,研究出了MCADAMA算法。通过搭建QAM盲均衡系统平台,把MCADAMA算法和其他3种恒模算法进行了比较,仿真结果表明,MCADAMA算法具有更快的收敛速度和更低的误码率,有效地提高了系统性能。     

一种新型变步长CMA盲均衡算法

针对传统固定步长CMA盲均衡算法中收敛速度和剩余误差这对矛盾,提出了一种新型变步长恒模盲均衡算法,即由瑞利分布函数实施对其步长的调节,通过调整该步长公式中的两个参数以加快收敛速度和减小剩余误差,并且在此基础上对该算法进行了改进。用4QAM信号,通过典型电话信道对固定步长的CMA算法,基于瑞利步长的CMA和改进后的CMA算法进行计算机仿真。通过对仿真出的算法收敛曲线以及输出星座图进行分析,最终得出在瑞利步长算法的基础上改进后的CMA算法克服了前两种算法的缺点,即具有收敛速度更快,剩余误差更小的优点。     

Blind equalizer for constant-modulus signals based on Gaussian process regression

A new blind equalization method for constant modulus (CM) signals based on Gaussian process for regression (GPR) by incorporating a constant modulus algorithm (CMA)-like error function into the conventional GPR framework is proposed. The GPR framework formulates the posterior density function for weights using Bayes' rule under the assumption of Gaussian prior for weights. The proposed blind GPR equalizer is based on linear-in-weights regression model, which has a form of nonlinear minimum mean-square error solution. Simulation results in linear and nonlinear channels are presented in comparison with the state-of-the-art support vector machine (SVM) and relevance vector machine (RVM) based blind equalizers. The simulation results show that the proposed blind GPR equalizer without cumbersome cross-validation procedures shows the similar performances to the blind SVM and RVM equalizers in terms of intersymbol interference and bit error rate.     

Nonsingular Constant Modulus Equalizer for PDM-QPSK Coherent Optical Receivers

Adaptive electronic equalizers using the constant modulus algorithm (CMA) algorithm often converge to a singular coefficient matrix that produces the same signal at multiple outputs. We address this issue in the context of optical communications systems with polarization-division multiplexing and coherent receivers. We study, by computer simulation, the performance of multiuser CMA equalizer, an enhanced CMA equalizer initially proposed for use in wireless multiuser and later multiple-input/multiple-output communications systems. We show that the proposed adaptive electronic equalizer does not exhibit singularities and, therefore, is superior to the commonly used CMA equalizer.     

一种并行的软判决引导常数模盲均衡算法

介绍了一种常数模与软判决引导结合的盲均衡算法CMA SDD。该算法克服了CMA收敛速度慢、稳态误差大的缺点,同时可以纠正相位偏转。仿真表明,在高信噪比(SNR)条件下,两种算法的稳态均方误差相近,而CMA SDD算法的收敛速度更快;在低信噪比条件下,CMA SDD算法可以获得更快的收敛速度和更低的稳态均方误差。     

A Blind Equalizer Based on Unsupervised Gaussian Cluster Formation with an Adaptive Non—Linearity

In this paper we present a blind equalizer algorithm based on an unsupervised Gaussian cluster formation technique with an optimized gradient adaptive step-size to update the equalizer coefficients.The novelty of this work lies in the optimization of the nonlinearity of the cluster formation used to achieve an optimal soft decision.The proposed iterative procedure combined with the variable step-size gradient-based adaptation,significantly accelerates the convergence speed of the blind equalization.The advantages of the proposed equalization techniques are illustrated by simulation.Simulation results obtained are compared with the Sato and Godard blind equalizers.