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。      

基于辅助数据的SC-FDE系统频域LS信道估计

通过对单载波频域均衡(SC-FDE)系统的分析得出了对最小二乘(LS)信道估计中采用的训练帧的要求, 从理论上推导了不计循环前缀(CP)能量损失的条件下, SC-FDE系统采用LS方法估计信道的性能界。文中指出, Newmann序列适合作为SC-FDE系统频域LS信道估计的训练帧。理论分析和仿真结果都表明, 采用Newmann序列可以达到LS信道估计的性能界。     

地空通信中基于贪婪算法的SC-FDE系统稀疏信道估计

针对在地空频率选择性衰落信道中,信道冲激响应具有时域稀疏特性的情况,提出了基于贪婪算法的单载波频域均衡(SC-FDE)系统稀疏信道估计方法。Chu序列是SC-FDE中常用的导频序列,对其进行分析并证明了将Chu序列进行循环移位所构造的导频矩阵满足RIP条件,将导频矩阵作为测量矩阵,把地空信道估计问题建模为稀疏重构模型,采用贪婪算法中的OMP和Co Sa MP算法对信道进行稀疏重构,仿真验证了所得信道估计较传统最小二乘(LS)信道估计方法更加准确。在相同的训练序列长度和信道环境下,利用所得信道估计对接收信号进行最小均方误差(MMSE)均衡,蒙特卡罗仿真结果表明,所提方法与传统LS信道估计方法相比,系统误码性能提高2~3 d B。     

基于NI USRP-RIO平台的MIMO-OFDM信道估计研究与实现

基于NI通用软件无线电平台(USRP-RIO),完成了MIMO-OFDM通信系统物理层设计,重点编写了信道估计相关的LabVIEW程序,分析并验证了经典频域LS信道估计和时域LS信道估计算法的性能。测试数据表明,在基于对数距离路径损耗模型的莱斯衰落信道环境下,时域LS信道估计误码性能优于频域LS信道估计,这一结果和理论分析相吻合,并且验证了系统实现的正确性。     

短波SC-FDE系统中改进的LS信道估计算法

针对短波单载波频域均衡( SC-FDE)系统中最小二乘( LS)信道估计算法受噪声影响大而导致的估计精度低的问题,提出了一种改进的基于小波去噪的LS信道估计算法。改进算法采用基于分块导频的帧结构,首先用LS算法对信道进行初步估计,然后根据小波多分辨率分析( Mallat)理论将LS估计的结果分解,并设置一个合理阈值对分解得到的小波系数处理,从而消除LS估计的残留噪声,提高估计精度。仿真结果表明,在短波信道下,改进算法不仅减小了系统开销,而且提高了LS估计的性能。     

一种基于预处理的OFDM低复杂度频域线性均衡算法

针对高频段OFDM无线传输系统中严重的载波间干扰（Inter-Carrier Interference,ICI）,提出了一种基于预处理的低复杂度频域线性均衡算法.在接收端先对各时刻的信道响应提取时变因子,进行一维时域滤波预处理;再用带状结构去近似提取时变因子后信道的频域矩阵,进行频域线性均衡.仿真结果表明,相对于MMS...     

水声信道中的迭代分组判决反馈均衡器

 与传统的时域均衡相比,频域均衡为单载波传输系统提供了一种计算更为有效的方法。该文对有大多径时延和多普勒频移的水声信道中的频域分组迭代判决反馈均衡器(IB-DFE)进行了研究,提出了一种联合迭代均衡和频域信道估计(JECE)算法,分析了JECE算法的性能以及不同数据参数对IB-DFE性能的影响,并计算了IB-DFE的计算复杂度。仿真结果表明,所提出的JECE算法对时变水声信道有更好的适应性。与TD-DFE相比,IB-DFE有3.6 dB以上的信噪比增益和约19%的复杂度增益,而且随着多径时延和多普勒频移的增加,这种性能增益会进一步增加。     

基于OFDM循环前缀LS信道估计的构造方法

提出了一种在正交频分复用系统中循环前缀频域序列（CPFS）用于最小二乘信道估计的子载波构造方法。该构造方法基于比较CPFS序列和梳状子载波序列的相关性,可使LS信道估计的精度增加。该相关性利用凸优化的方法,以子载波总体为变量及LS信道估计的最小均方误差（MSE）机制建立约束,得到优化模型并通过拉格朗日方法求得最终构造解。仿真验证表明,该构造方法得出子载波新解能使得LS估计模型下,CPFS序列的估计精度更优。     

基于导频和修正Kalman滤波的MIMO-OFDM信道估计方法

提出了一种适用于时间频率选择性衰落信道的MIMO-OFDM系统的组合信道估计方法。采用AR过程对信道进行建模,利用基于导频的低维Kalman滤波算法进行信道估计,并采用LS算法估计时变的信道衰减因子。Kalman滤波跟踪了信道的时域相关性,为了同时跟踪信道的频域相关性,采用了一种基于MMSE(minimum mean square error)的合并器对Kalman滤波算法进行修正。仿真表明,提出的这种组合算法降低了传统的Kalman滤波结构的复杂度,能够跟踪信道的时频变化,改进了基于LS准则的信道估计算法,并且与复杂的高维Kalman滤波算法的信道估计性能相当。     

维特比均衡算法

基于符号级维特比译码算法,将信道等效为一时变卷积编码器,提出了一种将信道均衡和信道译码相结合的技术——维特比均衡。重点研究了采用维特比均衡技术的单载波系统,并对比给出了采用频域均衡技术和维特比均衡技术,系统误码性能随信噪比的变化曲线及系统的计算复杂度。仿真结果表明：信道的等效脉冲响应滤波器长度较长时,维特比均衡技术明显改善了系统的误码性能,然而系统的复杂度也随之增加。     

单载波频域均衡信道估计分析

针对高速率信息传输系统中多径衰落对单载波频域均衡(SC-FDE)信道估计造成的影响,在SC-FDE原理基础上,将无线通信中信噪比估计和SC-FDE中信道估计结合起来,对现有信噪比估计算法进行优化。分析和仿真结果表明,此方法能有效地改善多径衰落信道中信道估计的有效性,提高了频域均衡的效果,从而改善了SC-FDE系统的误码率(BER)性能。     

The research on channel estimation and signal-noise ratio estimation based on minimum error entropy kalman filter for single carrier frequency domain equalization system

In this paper, the channel estimation and signal-to-noise ratio (SNR) estimation technique of single-carrier frequency domain equalization (SC-FDE) system under low SNR in aeronautical multipath channel are studied, a SNR estimation algorithm which is easy to implement in engineering and an improved LS channel estimation algorithm based on Kalman filter using minimum error entropy (MEE-KF) are proposed. This paper first introduces the SC-FDE system and introduces the principle of MEE-KF, and then, the channel estimation flow based on MEE-KF is obtained by combining it with the traditional LS channel estimation algorithm, which makes the estimation results perform better. Simulation results show that after getting more accurate noise variance, the channel estimation results can better follow the changes of the channel after MEE-KF processing, so as to resist the doppler frequency offset effect and make the channel estimation results more accurate, that is the channel response results of the data part can be closer to the real situation, so that the communication performance of SC-FDE system has also been greatly improved.     

Particle filtering based channel estimation in OFDM power line communication

Particle filtering （PF） algorithm has the powerful potential for coping with difficult non-linear and non-Gaussian problems. Aiming at non-linear, non-Gaussian and time-varying characteristics of power line channel, a time-varying channel estimation scheme combined PF algorithm with decision feedback method is proposed. In the proposed scheme, firstly the indoor power line channel is measured using the pseudo-noise （PN） correlation method, and a first-order dynamic autoregressive （AR） model is set up to describe the measured channel, then, the channel states are estimated dynamically from the received signals by exploiting the proposed scheme. Meanwhile, due to the complex noise distribution of power line channel, the performance of channel estimation based on the proposed scheme under the Middleton class A impulsive noise environment is analyzed. Comparisons are made with the channel estimation scheme respectively based on least square （LS）, Kalman filtering （KF） and the proposed algorithm. Simulation indicates that PF algorithm dealing with this power line channel estimation difficult non-linear and non-Gaussian problems performance is superior to those of LS and KF respectively, so the proposed scheme achieves higher estimation accuracy. Therefore, it is confirmed that PF algorithm has its own unique advantage for power line channel estimation.     

基于深度学习的单载波频域均衡算法研究

单载波频域均衡(Single-Carrier Frequency-Domain Equalization,SC-FDE)是一种有效的抗码间干扰的算法,在无线通信系统中得到了广泛的应用.传统线性SC-FDE算法主要包括信道估计、噪声功率估计和信道均衡三个模块,其中每个模块都是单独优化的.为了联合优化这三个模块,本文提出了...     

OFDM系统导频信道估计算法的性能研究

研究基于块状导频的最小平方（LS）信道估计、线性最小均方误差（LMMSE）和低秩LMMSE信道估计算法,并进行了算法仿真,得出不同信道估计算法下正交频分复用（OFDM）系统误比特率（BER）和信噪比（SNR）之间的变化关系,以及在不同导频符号间隔下的误比特率曲线图。仿真结果表明：LMMSE、低秩LMMSE和LS算法的性能依次变差,且导频符号间隔对误比特率性能影响较大。     

MIMO-OFDM信道估计仿真实现

正交频分复用（OFDM）可以有效地将频率选择性衰落信道转化成多个并行平坦衰落信道,从而大大提高传输效率。多输入多输出正交频分复用（MIMO-OFDM）技术可以大幅度地提高无线通信系统的信道容量与传输速率,其信道估计精度对系统性能有着直接的影响。研究了基于导频插入的SISO-OFDM和MIMO-OFDM最小二乘法估计（LS）信道估计方法。采用广义平稳非相关散射下的多径时变瑞利信道模型,对各个算法进行了仿真试验,得出不同算法下信道估计的误比特曲线,比较了各个算法的性能。仿真结果表明：MIMO-OFDMLS算法在误码率性能上优于SISO-OFDM。     

G3-PLC系统压缩感知信道估计的LS-SAMP算法

为了提高G3-PLC系统可靠性,引入压缩感知(Compressed Sensing,CS)的信道估计方法,提出了一种基于最小二乘(Least Squares,LS)的稀疏度预测自适应匹配追踪(LS Based Prediction-Sparsity Adaptive Matching Pursuit,LS-SAMP)算法。该算法在稀疏度自适应匹配追踪(Sparsity Adaptive Matching Pursuit,SAMP)算法的基础上,采用了基于LS的稀疏度预测方法对信道稀疏度进行预估计,使算法可以快速逼近信道的真实稀疏度,提高算法运行效率;其次利用主成分分析方法对观测矩阵进行线性优化,降低观测矩阵相干度,提高算法的重构性能。实验结果表明,在误码率为10-3时,所提算法相对于LS算法的信道估计性能有1 dB的提升,且其运行效率比SAMP算法提升了31.23%,以更有效的方式提高了G3-PLC系统的可靠性。     

Performance Analysis of Tikhonov Regularized LS Channel Estimation for MIMO OFDM Systems with Virtual Carriers

In this paper the effect of virtual carriers (VCs) on channel estimation performance is considered for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. The link between the number of VCs and the inverse problem in a conventional LS channel estimation is identified. It is observed that a linear increase in VCs contributes to an exponential increase of the system inverse problem as the condition number of the inverse matrix is exponentially increased. A solution is proposed using a low complexity modified LS channel estimation. The performance analysis of the modified LS channel estimation, regarding the effect of VCs, show gains in both the mean square error (MSE) performance of channel estimation as well as bit error rate (BER) system performance compared to conventional LS. The performance is improved irrespective of the increasing number of VCs as the estimator is shown to be insensitive to the increase of VCs in the OFDM system. The complexity reduction is also considered and an approach is proposed showing a similar complexity as LS.     

Performance evaluation of conventional and wavelet based OFDM system

In this paper we have compared the bit error rate (BER) performance and power spectral density of Discrete Fourier Transform (DFT) based OFDM system with wavelet based OFDM system. We also compared the performance of Least Square (LS) and Linear Minimum Mean Square Error (LMMSE) channel estimation technique for wavelet based OFDM system as well as DFT based OFDM system.