一种改进的基于DFT的OFDM信道估计算法

传统的DFT信道估计算法计算复杂度比MMSE算法低,性能比LS算法好。但是它只消除了信道冲击响应中循环前缀长度之外的噪声,而循环前缀长度以内的噪声并没有进行任何抑制,从而影响了算法的性能,说明性能存在提高的空间。对传统的DFT信道估计算法略加改进,仅仅在循环前缀长度内引入阈值门限,通过阈值门限进行阈值处理,就可以进一步消除噪声的影响。仿真表明：改进后的算法性能明显优于原算法,具有很好的实用价值。     

基于DFT的OFDM系统信道估计改进算法

基于DFT的信道估计算法计算复杂度比MMSE算法低,性能比LS算法好.但是传统的基于DFT的信道估计只消除了信道冲击响应估计中循环前缀长度之外的噪声,循环前缀长度内的噪声并没有得到抑制,因此算法性能还有提高的空间.本文提出了一种改进的基于DFT的信道估计算法.算法首先估计出噪声方差,然后利用噪声方差设定一个门限,通过此门限对循环前缀内的信道时域冲击响应值进行阈值,进一步消除噪声的干扰.仿真证明,本文的改进信道估计算法性能优于原算法.     

一种改进的水声正交频分复用稀疏信道时延估计算法

水声正交频分复用(OFDM)系统中,采用传统正交匹配追踪(OMP)方法估计离网格(off-grid)时延时,需要很高的过采样因子和高昂的计算开销.针对传统OMP方法估计离网格时延计算复杂度高的问题,该文借鉴多元线性拟合思想引入路径补偿的概念,提出了一种基于路径补偿的改进OMP时延估计算法,用以补偿从离网格路径向其周围网格位置泄漏的能量,并用补偿距离这一参数来解释路径补偿效果.该算法无需增加过采样因子,仅利用恰当的补偿距离即可实现较好的估计效果,且能在提高估计性能的同时降低计算复杂度.仿真分析与海试结果验证了该方法的优越性.     

基于DFT的短波OFDM系统信道估计改进算法

传统的DFT算法利用信道估计冲击响应的长度小于循环前缀长度的原理,滤除了循环前缀码长度以外的噪声,循环前缀内的估计值仍存在噪声,结合传统DFT信道估计算法,提出了一种短波OFDM系统的基于DFT的改进信道估计算法,此算法首先进行传统的DFT信道估计算法,滤除部分噪声信号。再根据信道脉冲响应的幅值选取幅值最大的Ng/2个信号作为有用信号,然后用DFT得到的估计值的平均值替换其余Ng/2个信号,最后得到基于DFT改进算法的信道估计信号。仿真结果表明该算法性能有很大提高。     

OFDM系统迭代信道估计初始值预测的改进算法

为了得到更精确的迭代信道估计中的信道初始频响值,在基于二次曲线拟合预测的OFDM系统联合迭代信道估计与符号检测算法的基础上,提出一种基于MMSE准则的加窗线性预测方法对信道的初始频率响应值进行估计.仿真结果表明,在较高信噪比下,文中提出的基于MMSE准则的加窗线性预测的估计方法所得到的系统误码性能明显优于采用二次曲线拟合预测的信道估计方法.在复杂度增加不大的情况下,该方法是一种有效的改进算法.     

Improved ML Channel Estimation for Uplink MC-CDMA Systems in Closely Spaced Multipath Channels

In order to attain near-single user performance in uplink multicarrier code- division multiple-access (MC-CDMA) systems, multiuser detection (MUD) methods may be employed which rely on simultaneous estimation of the channel frequency responses of multiple users. Pilot symbol assisted (PSA) channel estimation is needed in fast fading channels and it can be performed either by applying maximum likelihood (ML) criterion or minimum mean-squared error (MMSE) criterion. The performance of ML estimation technique degrades significantly in the case of fractionally spaced (FS) multipath channels where dominant paths are closely spaced with respect to the time resolution of the system. In such situation, the number of effective paths (which contribute more towards signal power) becomes considerably less than the actual number of multipaths at low and moderate SNR values. We propose an improved ML estimation method which considers only effective paths during the estimation process. The proposed method performs nearly identical to the MMSE estimation method and it can also provide significant reduction in the computational complexity when a large number of users are accommodated in the system.     

一种改进的LTE下行系统信道估计算法

基于3GPP长期演进（LTE）下行链路系统,在比较了现有几种不同信道估计算法的基础上,提出了一种适用于LTE下行系统的时频二维联合维纳迭代滤波信道估计算法。具体步骤如下：首先,采用基于奇异值分解（SVD）的线性最小均方误差（LMMSE）算法在频域进行维纳迭代滤波;然后,再利用频域估计出来的值在时域进行一次维纳迭代滤波。仿真结果表明,该算法能够有效地改善信道估计的误比特率（BER）性能,与传统的方法相比,性能更加接近于理想信道估计,同时也没有显著增加算法的运算复杂度。     

Iterative Decomposed OFDM Channel Estimation Algorithm Over Highly Mobile Channels

In orthogonal frequency-division multiplexing systems, the temporal channel gains to estimate are much more than the observable data over highly mobile channels. The basis expansion model (BEM) has been employed to reduce the number of these channel parameters. In the absence of channel statistics, generalized complex-exponential BEM (GCE-BEM) is popular for its fast algebra operation and easy generation of basis matrix. However, there is still much potential for performance improvement by modeling error reduction. In this paper, the factors affecting the modeling error are analyzed and an iterative decomposed estimation algorithm is proposed to improve the modeling accuracy. The proposed algorithm decomposes each tap into the linear part and the non-linear part. The linear part with two parameters (the middle value and the slope) is initialized by estimation in linearly time-varying channel models. And the non-linear part is addressed by the conventional least-squares (LS) method based on GCE-BEM and then the slopes of the linear part are updated for the next iteration by two distinct slope update methods. The simulations show that the proposed algorithm outperforms the conventional estimation methods with significantly reduced modeling error under both high signal to noise ratio and Doppler shift conditions.     

一种改进的OFDM系统盲信道估计算法

在OFDM通信系统中,信道参数估计一直是个备受关注的问题。本文利用接收端分集,提出了一种改进的盲信道估计算法,它适用于有无虚拟子载波,有无循环前缀的各种情况,在一定的信道精度要求条件下,可以在一个OFDM 符号内进行信道估计。计算机仿真显示,在积累相同的接收符号时,本算法也比同类的盲信道估计算法的性能好。     

基于改进SAMP算法的UWB多径信道估计

稀疏度自适应匹配追踪（SAMP）算法重构过程中存在其迭代终止条件设置不够合理的情况,需要对SAMP算法进行改进.在信道稀疏度未知时,改进SAMP算法依据残差之差的相对能量小于设定的停止门限来终止迭代过程,通过自适应调整可变步长逐步逼近信道的稀疏度,从而实现了重构UWB信道.仿真结果表明,改进SAMP算法低信噪比时重构精度高于SAMP算法,具有更好的重构性能和广泛的实用性.     

Analysis of DFT-Based Channel Estimators for OFDM

In this paper we analyze the performance of three low-complexity channel estimators, based on the discrete Fourier transform (DFT), for orthogonal frequency-division multiplexing (OFDM) systems. Estimators of this type have been analyzed for discrete-time channels, and we extend this analysis to continuous-time channels. We present analytical expressions for their mean-squared error (MSE) and evaluate their complexity vs. symbol-error rate (SER) for 16-QAM. The analysis shows that this type of estimators may experience an irreducible error floor at high SNRs. However, in one of the three estimators the error floor can be eliminated while the complexity stays low and the performance is maximized.     

一种改进的OFDM盲信道估计算法研究

信道估计在无线OFDM系统中至关重要,现有的盲信道估计算法中存在计算复杂度高、精度低的缺点。研究了一种改进的适用于SISO-OFDM系统的非冗余预编码的盲信道估计算法。在改进的算法中,由于采用幂法获得主特征值取代了原有采用特征值分解,使复杂度大大降低。仿真结果表明,改进的算法性能优于原有的基于预编码的盲信道估计算法。     

OFDM Signal Synchronization Algorithm in the Multipath Hydroacoustic Channel

The modified autocorrelation algorithm for synchronizing orthogonal frequency-division multiplexing signals propagating over acoustic underwater communications systems is examined, and analytical estimates of its accuracy are presented. It is demonstrated that the algorithm optimization under multipath channel conditions leads to modified window functions used to calculate likelihood functions. The suboptimal efficient variant of the algorithm based on rectangular windows is proposed.     

一种MC-CDMA最小二乘信道估计的改进算法

文中提出一种LS信道估计改进算法,该算法利用MC-CDMA中闲置的虚载波对信道噪声功率进行估计,通过将LS信道估计的时域响应限制在循环前缀长度内,并进一步利用信道噪声功率估计值,设置门限值忽略LS信道时域响应在循环前缀长度内的噪声分量和无效径响应。文中的算法运算量小,信道估计精度高,仿真结果验证了算法的有效性。     

快速时变信道下的OFDM信道估计方法

为解决正交频分复用(OFDM)系统在快速时变信道下引入的子载波间干扰(ICI)导致性能急剧下降的问题,提出一种基于带状矩阵的数据辅助型信道估计算法。通过分析由多普勒频偏引入的子载波间干扰矩阵,运用线性模型对信道冲击响应算法进行建模,对每个子载波设计带状补偿矩阵以最大程度消除ICI。数值仿真结果表明,该信道估计算法较最小均方误差(MMSE)算法复杂度大大减小,便于实现,满足快速时变信道下的估计精度需要。     

An Improved Multipath Channel Identification Algorithm Using Mulichannel Linear Prediction

Blind channel identification exploits the measurable channel output signal and some a priori knowledge of the statistics of the channel input signal. However, in many scenarios, more side information is available. In digital communication systems, the pulseshaping filter in the transmitter and the antialiasing filter in the receiver are often known to the receiver. Exploitation of this prior knowledge can simplify the channel identification problem. In this paper, we provide a thorough theoretical analysis on the linear prediction (LP)-based multipath identification approach. The analysis shows that the order overdetermination greatly deteriorates the performance of the LP multipath identification approach. This article, then, proposes an effective approach to detect the order of the multipath channel and alleviate the performance degradation attributed to the channel overmodeling. The obtained results demonstrate that the proposed approach offers substantial performance gain.     

一种改进的稀疏信道估计算法

文中在匹配跟踪算法的基础上实现了一种稀疏信道估计的改进算法。该算法首先通过正交匹配跟踪得到信道非零抽头的粗略估计,并依此来设置自适应均衡器的权重系数的初始值,进行自适应的调整和校正,最终实现对实际信道冲激响应的精确逼近。这样不仅避免了对无谓零抽头的估计,而且提高了信道估计的性能。     

一种改进的基于导频的OFDM信道估计算法

文中对OFDM（正交频分复用）系统中基于导频的信道估计技术进行了研究。MMSE（最小均方误差估计）算法有很好的性能但复杂度大,LS（最小二乘法估计）算法复杂度低但性能受到限制,在综合考虑性能和复杂度的情况下介绍了两种改进方法。并针对基于梳状导频的二项插值算法的缺陷,提出了一种改进的算法,计算机仿真证明了改进算法的误码率性能在高信噪比条件下高于原算法。     

信道估计在OFDM中的应用

介绍了信道估计在OFDM中的应用,提出一种易于实现的MMSE算法,并对MMSE和LS的性能进行了比较,同时研究了它们的改进算法。结果表明改进算法有很好的性能,可以逼近理想估计。在系统的实现中有较好的参考价值。