无人机数据链路信道LMS和RIS自适应均衡性能比较

通过时LMS和RLS自适应算法在无人机数据链路不同信道特性均衡中的应用进行研究，得出了两种均衡算法在对于不同信道均衡效果的差异，给出了两种均衡算法的最佳应用条件。     

快速启动自适应均衡算法的研究

研究一种快速启动自适应均衡算法,提出并证明了一个命题。计算机模拟结果表明:快速启动均衡算法总是优于LMS算法,固定信道中,性能甚至优于RLS算法;时变信道中,性能接近RLS算法。文中的快速启运自适应均衡算法,具有训练时间较短(与LMS算法比较)、运算简单、容易实现的特点,是一种比较实用的均衡算法。     

SIMO信道组合优化递推序列检测算法

传统的盲均衡算法主要基于高阶统计量(HOS)法或信道输出过采样的二阶统计量(SOS)算法，而这些算法不能实际应用于时变环境。与现有的自适应均衡LMS算法、RLS算法不同。提出了一种基于有限字符集信息的组合递推算法，实现单输入多输出(SIMO)信道盲序列检测。仿真表明：该算法具有较快的收敛速度和较低的稳态误码。     

光纤信道自适应均衡器的仿真研究

为了解决色散时光纤通信系统高速率、长距离传输的限制,在分析影响光纤通信系统性能的主要原因的基础上,提出一种光纤信道仿真模型,并用MATLAB仿真LMS算法和RLS算法对10 Gb/s光纤信道进行自适应均衡的性能.仿真结果表明,这两种算法简单、高效,能有效消除光纤色散和偏振模色散(PMD)引起的码间干扰,RLS算法比LMS计算复杂度高,但收敛速度更快,所以这两种算法都能满足光纤通信系统对均衡速度较高的要求.     

低空无线信道建模及其均衡技术研究进展

在介绍航空信道建模基础上 ,借鉴地面移动信道研究成果,分析了描述低空无线信道特性的常用参数,对不同场景下低 空信道的多径时延、多普勒频移等传输特性作了详细介绍,给出了低空信道建模的一般模型 。介绍了低空无线信道常用的LMS、RLS、CMA 三种信道均衡算法。最后,对低空无线信道建模研究以及适合低空信道的均衡算法进行展望 , 指出在改进现有均衡算法、编码和均衡相结合、最大多普勒估计和自适应均衡相结合等方 面是值得关注的研究内容。     

基于LMS及RLS的自适应均衡算法仿真分析

在通信系统中采用均衡技术是改善信道特性行之有效的方法,为此从时域均衡原理出发,讨论了基于LMS和基于RLS的自适应均衡算法,并利用Matlab对两类算法进行了仿真,从均衡前后信号的星座图、算法收敛特性以及均衡前后系统的误码特性这三个方面对两类算法的性能进行了比较.     

一种新型自适应均衡算法—RLS结合型算法

本文根据RLS算法和自适应均衡的特点,提出了一种新的自适应均衡算法——RLS结合型算法,并通过在短波信道上模拟判决反馈均衡器(DFE)研究了其性能。新算法是这样工作的:在训练方式,采用RLS算法;在传输方式,采用近似RLS算法。分析和计算机模拟结果表明:新算法的收敛速度和RLS算法一样快,稳定性和计算效率均优于RLS算法。     

无人机数据链路信道LMS和RLS自适应均衡性能比较

通过对LMS和RIS自适应算法在无人机数据链路不同信道特性均衡中的应用进行研究,得出了两种均衡算法在对于不同信道均衡效果的差异,给出了两种均衡算法的最佳应用条件。     

改进型RLS算法用于信道估值与信道均衡的比较

文对用于信道估值和信道均衡的几种改进型RLS算法进行了比较,理论分析和计算机仿真结果说明信道估值的最优解可以模拟出信道的传输函数,噪声仅对自适应滤波算法的收敛过程产生影响,而信道均衡的最优解受噪声功率谱密度的限制。因此性能良好的信道估值算法可以用于信道均衡中,以改善自适应均衡的性能。     

自适应滤波算法LMS和RLS及其在应用中的性能

本文介绍了最小均方误差(LMS)算法和递推最小二乘(RLS)两种自适应滤波理论,并在自适应均衡和信道估计两个应用领域中进行了MATLAB仿真结果.     

A novel variable step size adjustment method based on channel output autocorrelation for the LMS training algorithm

The least mean squares (LMS) algorithm, the most commonly used channel estimation and equalization technique, converges very slowly. The convergence rate of the LMS algorithm is quite sensitive to the adjustment of the step‐size parameter used in the update equation. Therefore, many studies have concentrated on adjusting the step‐size parameter in order to improve the training speed and accuracy of the LMS algorithm. A novel approach in adjusting the step size of the LMS algorithm using the channel output autocorrelation (COA) has been proposed for application to unknown channel estimation or equalization in low‐SNR in this paper. Computer simulations have been performed to illustrate the performance of the proposed method in frequency selective Rayleigh fading channels. The obtained simulation results using HIPERLAN/1 standard have demonstrated that the proposed variable step size LMS (VSS‐LMS) algorithm has considerably better performance than conventional LMS, recursive least squares (RLS), normalized LMS (N‐LMS) and the other VSS‐LMS algorithms. Copyright © 2011 John Wiley & Sons, Ltd.     

IEEE802.16a单载波频域均衡方案的仿真

研究了IEEE802.16a宽带无线接入系统的单载波频域均衡(SC-FDE)方案,建立了完整的802.16a单载波频域均衡系统仿真平台,研究了SC-FDE系统的频域均衡、编码和分集增益.仿真结果表明,将SC-FDE系统与判决反馈均衡、信道编码或发送分集结合都能提高SC-FDE系统抗多径干扰的能力.     

Improved Soft Iterative Channel Estimation for Turbo Equalization of Time Varying Frequency Selective Channels

In this paper, we present computationally efficient iterative channel estimation algorithms for Turbo equalizer-based communication receiver. Least Mean Square (LMS) and Recursive least Square (RLS) algorithms have been widely used for updating of various filters used in communication systems. However, LMS algorithm, though very simple, suffers from a relatively slow and data dependent convergence behaviour; while RLS algorithm, with its fast convergence rate, finds little application in practical systems due to its computational complexity. Variants of LMS algorithm, Variable Step Size Normalized LMS (VSSNLMS) and Multiple Variable Step Size Normalized LMS algorithms, are employed through simulation for updating of channel estimates for turbo equalization in this paper. Results based on the combination of turbo equalizer with convolutional code as well as with turbo codes alongside with iterative channel estimation algorithms are presented. The simulation results for different normalized fade rates show how the proposed channel estimation based-algorithms outperformed the LMS algorithm and performed closely to the well known Recursive least square (RLS)-based channel estimation algorithm.     

Performance analysis of linear MIMO equalizers for multitone DS/SS systems in multipath channels

In [11] the combination of multitone modulation with direct sequence spectrum spreading has been introduced. The performance of a correlation receiver has been evaluated for a multipath channel. In [12] the analysis has been extended to the presence of a multiple access interference. In the present paper we analyze the equalization problem of such a system for a single user scenario. In order to understand the potential of the system we first investigate the steady-state behavior of the MIMO equalizer for an MMSE design. The investigation is carried out for an equalizer following a receiver made of a bank of filters matched to both the symbol shape and the channel, which is a two-path channel. Assuming BPSK symbols an exact expression of the bit error probability before and after equalization is obtained in the form of an integral by means of the characteristic function method. Next adaptive LMS and RLS structures are proposed. The performance of the RLS algorithm is demonstrated.Part of this work has been presented at ICC '95, Seattle, June 1995.This author would like to thank the Belgian NSF for its financial support.This author is a Research assistant of FRIA.     

LMS算法和RLS算法在水声信道通信系统中应用的比较

为了减小水声通信系统中存在的由于多径传播效应引起的符号间干扰,可在系统中使用线性均衡器。首先介绍了LMS算法和RLS算法基本原理,利用Matlab仿真软件,给出了两种算法在水声信道通信系统中的自适应均衡的仿真系统,并对这两种算法对于均衡器的影响进行了比较,最后对比较的结果进行了分析。     

一种符号间干扰下的超宽带发射参考接收机

该文在超宽带传统发射参考接收机的基础上,对时分多址方唏下諘数据传输速率时参考接收脉冲与数据接收脉冲波形都受到脉冲间干扰污染的相关接收机进行了分析,在此模型的基础上利用超宽带室内信道慢衰落的特点,采用少量无重叠的导频脉冲对模型系数进行估计,并用Volterr系统下的LMS箕法进行跟踪.采用求根法对存在二阶符号间干扰的系统辛行非线性均衡.用IEEE802.15.3a的室内多径信道模型仿真结果蠨明,采用该非线性均衡算法下接收机比线性均衡能更有效地克服符号间干扰.     

基于小波变换变步长LMS自适应信道均衡的新方法

结合变换域最小均方(LMS)和变步长LMS算法的优势,提出了一种基于小波变换的变步长LMS自适应均衡方法。该方法中步长调整函数采用了改进的Sigmoid函数,该函数具有简单且误差信号接近零时变化缓慢的特点。并且,在训练模式、判决引导模式以及混合模式下,将提出方法和传统均衡方法进行了仿真比较。结果表明,所提出的方法比传统的线性LMS算法、变步长LMS以及小波变换LMS收敛更快、性能更优。     

数字通信系统中自适应均衡技术的研究

克服数字通信系统码间干扰的有效方法就是在接收端采用均衡技术。文中给出了均衡问题的数学描述，综述了实现均衡的方法，讨论了基于LMS和基于RLS的自适应均衡算法，并通过MATLAB仿真比较了两类算法的性能。