Fractionally spaced equalization of linear polyphase channels andrelated blind techniques based on multichannel linear prediction

We consider the problem of linear equalization of polyphase channels and its blind implementation. These channels may result from oversampling the single output of a transmission channel or/and by receiving multiple outputs of an antenna array. A number of previous contributions in the field of blind channel identification have shown that polyphase channels can be blindly identified using only second-order statistics (SOS) of the output. In this work, we are mostly interested in the blind linear equalization of these channels. After some elaboration on the specifics of the equalization problem for polyphase channels, we show how optimal settings of various well-known types of linear equalization structures can be obtained blindly using only the output's SOS by using multichannel linear prediction or related techniques     

Direct blind MMSE channel equalization based on second-orderstatistics

A family of new MMSE blind channel equalization algorithms based on second-order statistics are proposed. Instead of estimating the channel impulse response, we directly estimate the cross-correlation function needed in Wiener-Hopf filters. We develop several different schemes to estimate the cross-correlation vector, with which different Wiener filters are derived according to minimum mean square error (MMSE). Unlike many known sub-space methods, these equalization algorithms do not rely on signal and noise subspace separation and are consequently more robust to channel order estimation errors. Their implementation requires no adjustment for either single- or multiple-user systems. They can effectively equalize single-input multiple-output (SIMO) systems and can reduce the multiple-input multiple-output (MIMO) systems into a memoryless signal mixing system for source separation. The implementations of these algorithms on SIMO system are given, and simulation examples are provided to demonstrate their superior performance over some existing algorithms     

基于多天线接收的空间分集盲均衡算法

基于多天线接收的空间分集技术与均衡技术相结合的空间分集均衡算法可以克服衰落带来的不利影响,有效提高通信系统接收端的性能。文中将多天线支路间的合并权值和均衡器的权值统一合并于盲均衡算法中的系数估计,形成一种新的空间分集盲均衡算法,该算法具有较小的实现复杂度和很好的均衡效果。通过仿真实验表明,在误符号率相同的条件下,本文提出的分集均衡算法比单路信号盲均衡算法所需信噪比低1 dB-2 dB。同时分析了多天线接收的支路信号间存在的相位差以及延迟对算法的性能影响。     

一种基于二阶统计量的盲均衡算法

对于多输入多输出(MIMO)信道,使用有色输入的二阶统计量进行盲均衡是一种有效的方法.相对于原有的、基于自相关匹配原理的盲均衡算法,本文给出了一个在时域上不必先知道用户自相关序列值就能实现均衡的条件,并提出了相应的的时域均衡器训练算法,对含白噪声的情况也进行了讨论.     

MIMO blind equalization algorithm based on successive interference cancellation

Modified Constant Modulus Algorithm (MCMA) is widely used in the SISO blind equalization for its simplicity. For MIMO systems MCMA can only equalize one of the source signals. Through the combination of channel estimation and successive interference cancellation, source signals can be equalized in turn. However the recovery of the first source and the channel estimation are the key points, which directly affects the recovery of the subsequent sources. This paper proposes a channel estimation method with a small amount of calculation, and can accurately estimate the channel vector. Meanwhile, a new blind equalization algorithm is put forward to reliably recovery the first source signal. Simulation results verify the effectiveness of the proposed algorithm.     

Zero-forcing blind equalization based on subspace estimation formultiuser systems

Input signal recovery from frequency-selective fading channels is a problem of great theoretical and practical importance. We present several new blind algorithms that utilize second-order statistics for direct multichannel equalization. The algorithms are based on the subspace extraction of a preselected block column of the channel convolution matrix. For a multiuser system, user signal separation can be achieved based on partial information of the composite channel response. These equalization algorithms do not rely on the precise separation of signal and noise subspaces and therefore tend to be less sensitive to channel order (or column rank) estimation errors. Equalization is directly achieved without channel identification. Furthermore, the equalizability conditions of these algorithms are discussed     

基于子空间分解的多通道盲解卷积算法

针对卷积混合信号,提出了一种新的多通道盲解卷积算法,该算法首先利用子空间分解方法,将信号卷积混合模型变换成线性混合模型,然后利用线性混合盲分离算法分离出源信号.该算法相对频域盲解卷积算法来说无需解决线性混合盲分离中存在的幅度和排列顺序的模糊性问题,而且该算法不要求信号独立同分布,只要求各源信号统计独立即可.因此,该算法可以直接在中频对观察信号进行处理.计算机仿真结果表明,该算法不仅能对不同频不同调制方式的通信信号进行盲解卷积,而且对同频同调制的通信信号,该算法同样有效.     

一种基于CMA的变步长盲均衡算法研究

通信过程中因信道畸变而产生的码间干扰(ISI)严重影响通信质量,该问题常采用均衡技术来解决。介绍了传统定步长盲均衡CMA算法原理,仿真分析了其不能兼顾收敛速度快与稳态误差小的问题,为解决这一问题,提出一种基于Sigmoid函数的变步长盲均衡算法。为解决码间串扰问题,对CMA算法进行改进并对改进算法原理进行阐述,分析了参数对算法性能的影响。最后通过仿真实验证实了改进算法能够加快收敛速度,同时能保持较小的稳态误差。     

一种基于盲均衡的新均衡器算法及实现

基于简化星座图(RCA)的盲均衡算法提出了一种新的均衡器算法———RCA-LMS算法,有效地结合了RCA算法和传统的最小均方(LMS)算法的优点,并应用于选择性反馈均衡器(selective feedback equalizer,SFE)结构,实现了RCA-LMS选择性反馈均衡器(RCA-LMSSFE)。仿真结果表明,该均衡器在低信噪比条件下,能较快地收敛,有较小的稳态剩余误差,从而有效地减小了信号的码间干扰,提高了通信系统的抗干扰能力。     

一种基于切换步长的加权多模盲均衡算法

研究了常数模算法、多模算法、加权多模算法,并分析了各个算法的优缺点。针对加权多模盲均衡算法稳态误差小,但收敛速度慢的缺点,提出了一种基于切换步长的加权多模算法,最后对各算法在复信道环境下进行了仿真。结果表明,改进算法不受相位偏移的影响,而且在稳态误差基本不变的情况下,加快收敛速度。     

基于数据重用的集员滤波拟仿射投影盲均衡算法

传统常模盲均衡算法应用广泛但是其收敛速率很慢.为了满足在短突发数据条件下的信道盲均衡,提出一种基于数据重用的集员滤波拟仿射投影盲均衡算法.该算法将仿射投影思想结合到常模算法中,利用多数据向量同时提取信道信息,再附加改进的集员滤波算法有效减小了运算量,并结合数据重用思想重新设计所匹配的数据重用方式.仿真结果证明所提算法具有较快的收敛速率,与同类算法相比能提前700个迭代点收敛,且在信噪比为10 dB以上的信道环境中也有较好的效果,能够在短突发数据信道均衡中有效发挥作用.     

用于MQAM调制的双模式Sign-CMA盲均衡算法

在Sign-CMA算法基础上，提出了一种用于MQAM数字通信系统的双模式盲均衡算法。该算法克服了CMA算法稳态误差大的缺点，提高了Sign-CMA算法的收敛速度，并能纠正信道存在的相位旋转，实现载波恢复。     

Direct multiple-channel blind equalization

In this paper, the problem of blind channel identification and equalization is reviewed, and some recent results are presented.     

基于盲源分离的水声信道盲均衡处理方法

提出了一种基于盲源分离的水声信道讯均衡处理方法,通过对接收信号过采样构成源信号,采用了基于信息最大化原理(Infomax)在线分离算法进行了水声信道的盲均衡,并研究了时变水声信道条件下算法的均衡情况,仿真实验结果表明,该处理方法对多径水声信道具有较好的均衡效果,同时不受最小相位的条件限制。     

Decision directed adaptive blind equalization based on the constant modulus algorithm

In this paper, new decision directed algorithms for blind equalization of communication channels are presented. These algorithms use informations about the last decided symbol to improve the performance of the constant modulus algorithm (CMA). The main proposed technique, the so called decision directed modulus algorithm (DDMA), extends the CMA to non-CM modulations. Assuming correct decisions, it is proved that the decision directed modulus (DDM) cost function has no local minima in the combined channel-equalizer system impulse response. Additionally, a relationship between the Wiener and DDM minima is established. The other proposed algorithms can be viewed as modifications of the DDMA. They are divided into two families: stochastic gradient algorithms and recursive least squares (RLS) algorithms. Simulation results allow to compare the performance of the proposed algorithms and to conclude that they outperform well-known methods.     

基于粒子滤波器的盲辨识和盲均衡新方法

提出了一种新的基于粒子滤波器的盲辨识及盲均衡算法。在对信道进行辨识时，通过对信道均值的采样来代替对真实信道的采样，避免了对信道的后验密度进行采样，从而降低了算法的复杂度。算法还采用先验密度作为重要性函数，以便于对重要性函数进行采样。仿真结果表明，该算法收敛速度快，所需的数据量少，在信噪比较低时也能完成对信道的盲辨识和盲均衡。     

基于QAM调制信号的构造函数盲均衡算法

基于QAM调制信号及常模算法(CMA),提出一种新的盲均衡算法—构造函数(CF)算法。该算法通过构造一个函数,使得QAM信号幅度取值点为该函数的零点,再充分利用QAM信号的确定信息,提高算法的收敛速度和精度。计算机仿真结果表明,该算法克服了传输引起的QAM信号相位模糊(或相位偏移)问题,并能快速收敛,因此有较好的性能。     

基于预测原理的回声状态网络在线盲均衡算法

针对非线性信道,基于预测原理提出了回声状态网络(ESN)在线盲均衡算法,首先将具有良好非线性映射能力的ESN代替传统的线性预测误差滤波器,并采用递归最小二乘(RLS)算法计算网络的输出权值,使网络预测误差达到最小;然后进行幅值和相位的调整。仿真实验表明,对于16QAM信号,所提算法可以有效降低非线性信道对发送信号产生的畸变。与其他基于预测原理的盲均衡算法相比,所提算法有更低的均方误差值和更快的收敛速度。     

基于M22CMA的盲均衡算法仿真和实现

CMA算法具有结构简单、计算复杂度小且不占用额外的信道带宽的特点,在无线通信应用中正受到越来越广泛的关注。从CMA算法出发,推导了一种适用于复信号的M22CMA结构,使用QPSK信号对算法进行了Matlab仿真和VHDL验证。仿真和实验结果表明,该算法性能稳定,可用于无线信道中QPSK信号的均衡处理。     

Automatic equalization using transversal filters

The restriction that linear distortion imposes on the flow of information has been well known for some time. Consequently, means have been developed for reducing this distortion through the insertion of compensating linear devices. In the past this reduction has been achieved through the use of conventional lumped-parameter networks, quite static by nature. The use of the transversal filter, however, provides a more dynamic and flexible approach. This device is well suited to automatic and even adaptive operation, and thus it can meet the demands of a channel with time-varying distortion.