激光通信系统的波特间隔均衡器设计

当前应用的均衡器，主要采用单一的盲自适应算法实现信道均衡处理，容易出现误差扩散的现象，导致均衡器误码率较高。因此，针对激光通信系统，设计一种新的波特间隔均衡器。根据激光通信系统的接收端接收信号模型、干扰模型，定义激光通信系统信道模型。基于信道均衡要求，设计由前滤波器、反馈滤波器两个主要部分组成的多阶滤波器，作为波特间隔均衡器的基础结构。通过设置MSE切换门限联动LMS算法和CMA算法，形成自适应混合均衡算法，确保均衡器具有优越的信道均衡处理性能。最后，在FPGA上实现波特间隔均衡器。实验结果显示：应用所设计均衡器后，激光通信系统的最小误码率降低至10^-4,达到了提升激光通信质量的目的。     

用滤波器组构成的传送多路复用器结构实现MMSE盲信道均衡

冗余滤波器组构成的传送多路复用器可以用来对FIR信道进行估计和均衡.本文提出一种在FIR滤波器组框架结构下,首先利用信号的相关矩阵对信道进行估计,然后在此基础上用MMSE准则下设计的FIR均衡器对数据进行均衡的盲算法.该均衡算法的性能要明显好于基于ZF准则的方法,并且在消除ISI的同时可以抑制噪声的影响,从而使系统的输出信噪比达到最优,而增加的复杂度很有限.文中最后在两种典型信道下对所提出的盲信道均衡算法进行了仿真,结果验证了上述性能.     

离散混沌系统稳健差拍同步方法及其在保密通信中的应用

本文结合自适应信道盲均衡和离散混沌系统差拍同步提出了一种存在信道畸变时的离散混沌系统的稳健关拍同步方法。该方法把混沌误差同步作为能量函数,利用进化算法训练递归神经网络完成自适应信道盲均衡,均衡器的输出作为混沌接收器的激励信号,从而在完成信道盲均衡的同时混沌系统达到同步状态。此外,本文提出了一种利用离散混沌系统稳健差拍同步实现存在信道畸变时的保密通信方法。     

保密通信中稳健差拍同步方法的描述与验证

结合自适应信道盲均衡和离散混沌系统的稳健差拍同步提出了一种存在信道畸变时的离散混沌系统的稳健差拍同步方法.该方法把混沌误差同步作为能量函数,利用进化算法训练递归神经网络完成自适应信道盲均衡,均衡器的输出作为混沌接收器的激励信号,从而在完成信道盲均衡的同时混沌系统达到同步状态.此外,提出了一种利用离散混沌系统稳健差拍同步实现存在信道畸变时的保密通信的方法.     

一种应用粒子滤波器实现混沌通信的方法

该文研究应用粒子滤波器实现混沌通信的问题。组合信号建模技术,提出了一种基于粒子滤波器的实现方法。在发送端,采用加性混沌掩盖或乘性混沌掩盖将信息符号调制在混沌信号上;在接收端,应用粒子滤波器估计信息符号,进而实现混沌通信。仿真结果表明,当信息符号为二进制编码和M进制编码时,基于两种混沌掩盖的通信方案,粒子滤波器均能较好地从噪声混沌信号中恢复信息的编码值;与无先导卡尔曼滤波器相比,前者具有较低的误码率。此外,对比两种混沌通信方案,基于粒子滤波器的加性混沌掩盖通信系统在较高的Eb/N0下的通信性能接近BPSK,具有较低的误码率。     

基于粒子滤波的Turbo盲均衡

粒子滤波是一种基于贝叶斯估计的算法,在信道盲辨识和盲均衡问题上具有快收敛、抗深衰信道等优势。Turbo盲均衡在低信噪比条件下有较好的误码性能。为了在深衰信道下使通信具有良好的误码性能,对粒子滤波盲均衡算法进行改进,改进算法的重要性采样函数利用了粒子的先验信息,得到一种软输入软输出的粒子滤波盲均衡算法。依据Turbo盲均衡的框架结构实现了一种基于粒子滤波的Turbo盲均衡算法,该算法利用信道编码带来的编码增益,提高了均衡和信道辨识的性能。仿真结果表明相比粒子滤波盲均衡算法本文提出算法的误码率性能提高1dB左右,误帧率性能则提高了3dB以上,经分析可知在信道系数估计较为准确的条件下,系统数据帧几乎没有误码。      

MIMO-OFDM系统中的子空间半盲信道估计

本文主要讨论了MIMO-OFDM系统中的一种半盲信道估计算法.该算法基于子空间分解技术,利用信号子空间和噪声子空间的正交性将两者分离.针对盲信道估计存在计算量大及收敛速度慢等缺点,本文充分利用少量的导频,给出了一种基于子空间跟踪技术的半盲MIMO-OFDM信道估计算法.仿真结果表明,该算法在保持盲信道估计算法性能的基础上,明显加快了收敛速度、降低了计算量.     

信道均衡中的盲信号处理技术

在信号高速传输的过程中,由于耦合效应及多址干扰等因素的影响,数据通信会产生码问干扰,从而降低了数据信号的传输速度.现代通信技术中的信道均衡技术就是用于消除码间干扰和补偿信道,减小了误码率提高了通信的质量.信道均衡技术包括两个方面,一是自适应均衡技术,一是盲信道均衡技术.由于自适应均衡技术已经暴露出许多不足,因此盲均衡技术应运而生并以其具有的特殊优点越来越受到重视.本文介绍了码间干扰产生以及盲均衡技术的数学原理,并对几种常用的盲均衡算法进行了研讨.     

l0-范数约束的稀疏多径信道分数间隔双模式盲均衡算法

针对深衰落稀疏多径信道下多进制相移键控（Multiple Phase Shift Keying,MPSK）信号的盲均衡问题,提出了一种l₀-范数约束的分数间隔稀疏自适应双模式盲均衡算法.该算法借鉴传统的分数间隔双模式盲均衡算法思想,结合稀疏自适应滤波理论,首先利用l₀-范数对均衡器抽头系数进行稀疏性约束,构造出一种l₀-范数约束的分数间隔双模式最小均方误差代价函数,然后依据梯度下降法推导出盲均衡器抽头系数更新公式,并对迭代步长进行归一化和比例系数化.理论分析和仿真实验表明,与基于门限稀疏化的盲均衡算法、基于分数阶范数的盲均衡算法及分数间隔双模式盲均衡算法相比,本文所提算法在保证较快收敛速度的前提下,能有效降低剩余符号间干扰.本文设计的盲均衡算法为水声通信系统中接收方恢复出发送信号,提供了一种快速有效的方法.     

用于克服MIMO信道时变性的去相关自举均衡器

本文提出了一种用于克服MIMO信道时变性的自举均衡器.本文首先提出了用于MIMO通信系统的去相关均衡算法,该算法利用通信信源的统计特性实现不同源信号之间的去相关,从而克服了MIMO系统的同信道干扰.接着本文将去相关均衡算法用于时变的MIMO系统,提出了用于克服MIMO信道时变性的自举均衡器.该均衡器仅利用其输入信号来对时变的MIMO系统进行均衡,在仅增加很小的运算量的条件下,大大克服了因信道时变而在常规均衡器输出端产生的同信道干扰,提高了系统的误码性能.仿真实验证实,本文提出的去相关MIMO自举均衡器克服了信道时变的影响,明显改善了接收机的误码性能.     

A Supervised Constant Modulus Algorithm for Blind Equalization

Blind equalization is a technique for adaptive equalization of a communication channel without the aid of the usual training sequence. Although the Constant Modulus Algorithm (CMA) is one of the most popular adaptive blind equalization algorithms, it suffers from slow convergence rate. A novel enhanced blind equalization technique based on a supervised CMA (S-CMA) is proposed in this paper. The technique is employed to initialize the coefficients of a linear transversal equalizer (LTE) filter in order to provide a fast startup for blind training. It also presents a computational study and simulation results of this newly proposed algorithm compared to other CMA techniques such as conventional CMA, Normalized CMA (N-CMA) and Modified CMA (M-CMA). The simulation results have demonstrated that the proposed algorithm has considerably better performance than others.     

A Novel Interpolation Equalization Technique for Multicarrier Modulation/Demodulation Systems

This paper presents a novel multitap interpolation equalization technique for filter bank-based multicarrier modulation/demodulation systems. The proposed technique is based on the equalization of the channel fractional delay in each subchannel in time synchronization with the constituent receiver side decimator. The proposed synchronization is achieved by combining a subset of the polyphase components of the analysis filter output signal after having passed through a bank of interpolation equalizers. The resulting multitap interpolation equalization permits a trade-off between various equalization parameters, such as the number of used polyphase components, the length of the equalizer, and the interchannel interference terms, making it possible to achieve a high signal-to-noise ratio (SNR) involving moderate equalization cost or a moderate SNR involving very low equalization cost. Simulation results for the standard carrier serving area loop show that the proposed equalization technique gives rise to 15 dB improvement in SNR compared to the output combiner equalization technique and can achieve an SNR close to the matched-filter bound for the channel by employing a reasonable equalizer length. Compared to the output combiner equalization technique, the proposed equalization technique involves around three times less the storage requirement at the same computational cost or around three times less the computational cost at the same storage requirement for equalizer training. Two suboptimal solutions are also proposed to simplify the equalizer training at only a minor loss in SNR.     

Reconstruction of chaotic signals with application to channel equalization in chaos‐based communication systems

A number of schemes have been proposed for communication using chaos over the past years. Regardless of the exact modulation method used, the transmitted signal must go through a physical channel which undesirably introduces distortion to the signal and adds noise to it. The problem is particularly serious when coherent‐based demodulation is used because the necessary process of chaos synchronization is difficult to implement in practice. This paper addresses the channel distortion problem and proposes a technique for channel equalization in chaos‐based communication systems. The proposed equalization is realized by a modified recurrent neural network (RNN) incorporating a specific training (equalizing) algorithm. Computer simulations are used to demonstrate the performance of the proposed equalizer in chaos‐based communication systems. The Hénon map and Chua's circuit are used to generate chaotic signals. It is shown that the proposed RNN‐based equalizer outperforms conventional equalizers as well as those based on feedforward neural networks for noisy, distorted linear and non‐linear channels. Copyright © 2004 John Wiley & Sons, Ltd.     

基于多小波双变换的非线性卫星信道盲均衡算法

针对非线性卫星信道Volterra盲均衡系统收敛缓慢、计算复杂高等不足,提出了基于多小波双变换的非线性卫星信道盲均衡算法.该算法用Wiener均衡器代替Volterra均衡器,减小了均衡器结构的复杂性;用平衡正交多小波对Wiener均衡器的输入信号进行变换,降低了输入信号的自相关性;在Wiener均衡器输出端增加一级判决反馈滤波器,同时对其输入信号作平衡多小波变换,又降低了判决反馈滤波器输出信号的自相关性.仿真结果验证了该算法的有效性.     

Autocorrelation properties of channel encoded sequences-applicability to blind equalization

Many blind channel equalization/identification algorithms are derived assuming the transmitted information sequence to be white. In practical communication systems, redundancy is added to the source sequence in order to detect and correct symbol errors in the receiver. It is not obvious how channel encoding will affect the assumption of whiteness. The autocorrelation function of some commonly used channel codes is analyzed in order to study the validity of assumptions used in blind equalization. The codes are presented in terms of a Markov model for which the autocorrelation is analytically expressed. The various encoded sequences are used in a prediction error based blind equalizer, and the performance is empirically compared with the case of unencoded data. A blind equalization example using a practical GSM speech encoder combined with a convolutional channel encoder is also given.     

Blind adaptive spatial-temporal equalization algorithms forwireless communications using antenna arrays

Antenna arrays are used for diversity reception so as to improve the quality of wireless communication systems. To make full use of the information contained in each sensor, a spatial-temporal equalizer is used to remove intersymbol interference and mitigate the additive channel noise. This equalizer can be used in the wireless communication systems to improve the performance. This article introduces two blind adaptive algorithms for spatial-temporal equalization. Computer simulation demonstrates that the new algorithms converge faster than fractionally spaced constant-modulus algorithm (FS-CMA)     

基于RENYI熵的水声信道判决反馈盲均衡算法研究

在水下通信系统中,为了抑制由多径效应产生的严重码间干扰,必须进行信道均衡。针对传统的常数模判决反馈盲均衡(CMA-DFE)收敛速度较慢的问题,该文提出了一种基于RENYI熵的判决反馈盲均衡算法(RENYI-DFE)。该算法使用RENYI熵算法调节均衡器前向权向量,用CMA算法调节均衡器反馈权向量,与CMA-DFE相比,该算法在计算量增加很小的情况下,使得盲均衡算法的收敛速度显著增加。仿真结果证明了该算法的优越性。     

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.