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     

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     

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。     

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。     

两种改进的盲均衡算法

文献[1]提出了一种适用于PAM、QAM通信系统的盲均衡算法--MMA,该算法虽然克服了CMA收敛后剩余误差大和stop-and-go等算法有待定参数的缺点,但是它的收敛速度比较慢,改进算法1对MMA进行了改进,加快了算法收敛的速度.改进算法2是一种联合信道盲均衡和相位恢复算法--MCMA[2]的改进算法,改进后的算法比MCMA具有更小的剩余误差,同时在迭代过程中能够提供更准确的相位信息,来补偿信道引起的相位误差,从而更加有利于判决器进行准确的判决.两种改进算法都大大减少了使系统误符号率降为0所需的迭代次数.计算机仿真结果表明,这两种算法具有良好的均衡特性.     

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.     

一种新的基于数据可靠性判决引导的CMA盲均衡算法

本文在常数模算法（CMA）基础上,提出了一种适合于多电平正交幅度调制（MQAM）数字通信系统的基于数据可靠性判决引导的盲均衡算法。理论分析和计算机模拟表明,该算法具有较好的性能,是一种很实用的均衡算法。     

一种变步长双模式盲均衡算法的研究

在移动通信中,物体的高动态性引起多普勒频移,应用恒模( CMA)算法,不能克服波频率偏移引起的接收信号相位旋转.针对其存在的缺点,给出了一种变步长双模式盲均衡算法,该算法将修正常数模算法(Modify constant modulus algorithm,MCMA)和判决引导(Decision directed,DD)算法有机结合,不仅具有较快的收敛速度,而且能在去除码间干扰的同时有效克服相位旋转和一定范围的载波频率偏移,具有很好的实用性.通过计算机仿真验证了该算法的性能.     

An enhancement to blind equalization algorithms

Blind equalization performance can be improved by controlling the equalizer adaption step-size according to the region in which the received signal lies in the constellation plane. A simple technique based on this principle is proposed as a modification to blind equalization algorithms, and its effectiveness is demonstrated by simulation. As an example, the algorithm of Picchi and Prati (1987) is considered since it is simpler and converges faster. The proposed modification is applied to the zero-forcing (ZF) algorithm     

Convex cost functions in blind equalization

Existing blind adaptive equalizers that use nonconvex cost functions and stochastic gradient descent suffer from lack of global convergence to an equalizer setup that removes sufficient ISI when an FIR equalizer is used. The authors impose convexity on the cost function and anchoring of the equalizer away from the all-zero setup. They establish that there exists a globally convergent blind equalization strategy for 1D pulse amplitude modulation (PAM) systems with bounded input data (discrete or continuous) even when the equalizer is truncated. The resulting cost function is a constrained l₁ norm of the joint impulse response of the channel and the equalizer. The results apply to arbitrary linear channels (provided there are no unit circle zeros) and apply regardless of the initial ISI (that is whether the eye is initially open or closed). They also show a globally convergent stochastic gradient scheme based on an implementable approximation of the l₁ cost function     

Dual-mode type algorithms for blind equalization

Adaptive channel equalization accomplished without resorting to a training sequence is known as blind equalization. The Godard algorithm and the generalized Sato algorithm are two widely referenced algorithms for blind equalization of a QAM system. These algorithms exhibit very slow convergence rates when compared to algorithms employed in conventional data-aided equalization schemes. In order to speed up the convergence process, these algorithms may be switched over to a decision-directed equalization scheme once the error level is reasonably low. The authors present a scheme which is capable of operating in two modes: blind equalization mode and a mode similar to the decision-directed equalization mode. In this proposed scheme, the dominant mode of operation changes from the blind equalization mode at higher error levels to the mode similar to the decision-directed equalization mode at lower error levels. Manual switch-over to the decision-directed mode from the blind equalization mode, or vice-versa, is not necessary since transitions between the two modes take place smoothly and automatically     

Blind zero forcing equalization of multichannel nonlinear CDMAsystems

Code division multiple access (CDMA) has emerged as a popular format for wireless communication systems. As a result of intersymbol interference (ISI) and nonlinearities, the performance of CDMA systems can suffer. In this paper, we propose a blind equalizer for CDMA systems with Volterra (nonlinear) channels. The equalizer requires multiple observations at the receiver, which are obtained through oversampling or an antenna array, and a knowledge of the code of the desired user. Zero forcing equalization is possible in the noise-free case. Simulations demonstrate the performance of the equalizer under a variety of operating conditions     

Parametric optimization of multichannel rejection filters

The number of channels of a multichannel rejection filter (MRF) has been optimized by the energy and probabilistic criteria. The matrix of MRF coefficients is defined. The paper includes analysis of the gain in signal detection effectiveness, in the presence of interference, as compared to the single-channel rejection filter.