一种基于GY／T220．1-2006标准的OFDM信道估计算法

在卫星移动多媒体广播系统中,由于多普勒频移及多径影响,信道是时变的,需要估计出信道的时域或频域响应来消除时变信道对传输信号的影响。针对GY/T 220.1-2006标准的导频插入图案,提出了一种基于LS估计准则、在时间轴方向二维线性内插、频域轴方向变换域内插的信道估计算法。仿真结果表明,在不同多径信道的情况下,随着信噪比的增加,该算法的性能均优于最近插值、线性插值和低通滤波插值算法。该算法计算复杂度较spline插值和cubic插值低,适于硬件实现。     

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。     

一种MC-CDMA系统LS信道估计的改进算法

LS信道估计算法计算量小,实现简单,但是受噪声的影响信道估计精度低。为降低噪声对信道估计精度的影响,提出一种基于DFT的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通过设置门限值忽略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,显著提高了信道估计精度。本文的算法运算量小,实现简单,信道估计精度高,仿真结果验证了算法的有效性。     

基于RLS的MIMO OFDM自适应信道估计

依据最小均方误差准则提出了基于多相正交序列循环移位和基于重复相位旋转Chu两种训练序列设计方法,并给出了相应的最小二乘(RLS)自适应信道估计算法。首先用简单的LS算法对信道进行初步估计,然后采用RLS算法进行自适应滤波器提高信道估计的性能,最后,将滤波后得到的时域信道估计经过FFT变换为频域信道响应,并对OFDM数据符号进行频域均衡。与传统单一的信道估计技术相比,该方法具有较低的复杂度和较好的估计性能,仿真实验证明了该算法的有效性。     

一种适用于DCO-OFDM系统的DFT信道估计算法

针对直流偏置光正交频分复用系统中传统离散傅里叶变换(DFT)信道估计算法运算复杂度高和循环前缀(CP)内存在非有效信道系数的问题,提出厄米特对称的DFT(H-DFT)阈值改进信道估计算法。首先,根据信道时域响应变换到频域满足厄米特对称的性质,只需对有效子载波的信道频域响应做厄米特对称即可获得全部子载波的信道频域响应;其次,根据CP外噪声的平均功率对CP内的信道抽头数据设置阈值来滤除CP内的噪声。仿真结果表明:与传统DFT信道估计算法相比,H-DFT阈值改进信道估计算法有效降低了运算复杂度,在误比特率和均方误差方面也得到了明显的改善。     

压缩采样匹配追踪在水声MIMO-OFDM信道估计的应用

针对水声MIMO-OFDM系统,利用水声多径信道冲激响应的稀疏特性,提出一种基于压缩采样匹配追踪 (Compressive Sampling Matching Pursuit, CoSaMP)的信道估计方法。该算法首先利用观测矩阵构建一个向量代替信道,然后采用匹配追踪思想确定这个向量的非零抽头系数位置,最后利用最小二乘法对非零抽头系数进行估计,通过对该向量的估计实现信道响应的估计。与传统最小二乘法（least square, LS）相比,信道估计性能得到很大的提高,与正交匹配追踪（Orthogonal Matching Pursuit,OMP)相比,提高信道估计性能的同时,降低了计算复杂度。通过仿真分析,不但验证了该算法的有效性,还比较了该算法在不同通信系统中的信道估计性能。      

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.     

宽带MIMO-OFDM系统信道估计算法研究

本文提出了MIMO-OFDM系统中基于LS准则的参数化信道估计方法(LSPCE),推导出其MSE性能的下界并给出一种最优导频序列.为了降低复杂度,本文还提出了一种迭代的算法,它利用有限冲击响应信道的抽头之间的相关性从噪声中提取出信道信息并同时估计出多径时延.仿真和分析表明,相比传统的LS信道估计算法,这种基于参数化的信道估计算法可以大大提高信道估计的精度,接收端的检测性能接近理想信道估计的性能.     

无线OFDM系统中信道冲激响应有效阶数估计

在基于OFDM技术的无线通信系统中,针对LS信道估计算法时域结果的构成,同时结合无线信道冲激响应在时域为有限冲激响应的特点,提出对LS信道估计算法的时域结果进行能量检测,并实行逆向搜索以获得信道有效阶数估计值的算法。理论分析和计算机仿真表明此算法能够得到很好的无线信道有效阶数估计结果。     

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。     

Adaptive Channel Estimation Using Pilot-Embedded Data-Bearing Approach for MIMO-OFDM Systems

Multiple-input multiple-output (MIMO) orthogonal-frequency-division-multiplexing (OFDM) systems employing coherent receivers crucially require channel state information (CSI). Since the multipath delay profile of channels is arbitrary in the MIMO-OFDM systems, an effective channel estimator is needed. In this paper, we first develop a pilot-embedded data-bearing (PEDB) approach for joint channel estimation and data detection, in which PEDB least-square (LS) channel estimator and maximum-likelihood (ML) data detection are employed. Then, we propose an LS fast Fourier transform (FFT)-based channel estimator by employing the concept of FFT-based channel estimation to improve the PEDB-LS one via choosing a certain number of significant taps for constructing a channel frequency response. The effects of model mismatch error inherent in the proposed LS FFT-based estimator when considering noninteger multipath delay profiles and its performance analysis are investigated. The relationship between the mean-squared error (MSE) and the number of chosen significant taps is revealed, and hence, the optimal criterion for obtaining the optimum number of significant taps is explored. Under the framework of pilot embedding, we further propose an adaptive LS FFT-based channel estimator employing the optimum number of significant taps to compensate the model mismatch error as well as minimize the corresponding noise effect. Simulation results reveal that the adaptive LS FFT-based estimator is superior to the LS FFT-based and PEDB-LS estimators under quasi-static channels or low Doppler's shift regimes     

An Improved DFT-Based Channel Estimation Algorithm for OFDM System in Non-sample-Spaced Multipath Channels

It is well known that channel impairment caused by multipath reflections can deeply degrade the transmission efficiency in wireless communication systems. The conventional DFT-based channel estimation methods improve the performance by neglecting nonsignificant channel taps. However, in multipath channels with non-sample-spaced time delays, this will cause power leakage and result in an error floor. In order to overcome this problem, based on the property of Channel impulse response, we describe a utility of channel estimation technology for OFDM systems using discriminant analysis. Usually, significant channel taps are detected on the basis of a predetermined threshold, so the optimal threshold value becomes a crucial factor. But it is difficult to decide channel taps that are approximately equal to the threshold value. To solve this disadvantage, the proposed algorithm improves performance by using Mahalanobis distance discriminant analysis for channel taps. This approach can mitigate the aliasing effect in the DFT-based channel estimator and reduce the leakage power efficiently when there is non-sample-spaced path delay. Simulation results show that the proposed channel estimators can eliminate the error floor substantially and its performance is better than the LS and conventional DFT estimators.     

Sparse channel estimation and tracking for cyclic delay diversity orthogonal frequency division multiplexing systems

In cyclic delay diversity orthogonal frequency division multiplexing systems, the excessive channel delay spread and corresponding high frequency selectivity makes channel estimation a challenging task. In this paper, we propose a two‐stage scheme to estimate and track the highly frequency selective channel. At the preamble reception stage, least squares channel estimation with L₀ norm regularization is proposed to exploit the channel sparsity. At the data demodulation stage, an expectation–maximization algorithm with the most significant tap selection is developed to track channel variations by using the channel order obtained from the first stage. Compared with other estimation methods, the proposed scheme requires no prerequisite knowledge of delay parameter settings, which leads to more flexibility. Furthermore, the scheme can exploit the channel sparse structure by detecting the nonzero taps and, consequently, has better mean squared error performance. Simulation results show that the proposed estimation scheme can retain the provided diversity gain of cyclic delay diversity effectively in time‐varying fading channels. Copyright © 2011 John Wiley & Sons, Ltd.     

长时延扩展水声信道的联合稀疏恢复估计

对具有长时延扩展的水声信道,传统的信道估计算法如最小二乘法将在大量零值抽头产生严重的估计噪声,导致估计性能下降,同时信道估计时所需的较高估计器阶数大大提高了运算复杂度。压缩感知信道估计方法可有效利用多径稀疏特性改善性能,但需采用较大的训练序列长度以保证稀疏恢复精度,由此导致额外的系统开销。利用水声信道多径稀疏结构在数据块间存在的相关性,建立基于分布式压缩感知的长时延水声信道联合稀疏模型,从而可利用同步正交匹配追踪算法进行联合重构,以进一步减小系统的训练序列开销,提高估计性能。最后通过仿真和海上实验验证了所提方法的有效性。     

High‐resolution compressive channel estimation for broadband wireless communication systems

Broadband channel is often characterized by a sparse multipath channel where dominant multipath taps are widely separated in time, thereby resulting in a large delay spread. Accurate channel estimation can be done by sampling received signal with analog‐to‐digital converter (ADC) at Nyquist rate and then estimating all channel taps with high resolution. However, these Nyquist sampling‐based methods have two main disadvantages: (i) demand of the high‐speed ADC, which already exceeds the capability of current ADC, and (ii) low spectral efficiency. To solve these challenges, compressive channel estimation methods have been proposed. Unfortunately, those channel estimators are vulnerable to low resolution in low‐speed ADC sampling systems. In this paper, we propose a high‐resolution compressive channel estimation method, which is based on sampling by using multiple low‐speed ADCs. Unlike the traditional methods on compressive channel estimation, our proposed method can approximately achieve the performance of lower bound. At the same time, the proposed method can reduce communication cost and improve spectral efficiency. Numerical simulations confirm our proposed method by using low‐speed ADC sampling. Copyright © 2012 John Wiley & Sons, Ltd.     

Improved Channel Estimation Based on Parametric Channel Approximation Modeling for OFDM Systems

Orthogonal frequency division multiplexing (OFDM) together with high order modulation scheme requires accurate channel estimation to perform coherent demodulation. In this paper, improved channel estimation methods based on a parametric channel approximation model are proposed for the OFDM system using pilot subcarriers. This channel model is called fraction taps channel approximation (FTCA) model, which is defined as a finite impulse response (FIR) on some definitive delay taps that have a fraction tap delay spacing relative to the sampling interval. Then, based on the FTCA channel model, the minimum mean square error (MMSE) and least square (LS) estimators are derived. Simulations over non-sample-spaced channels prove that the use of the FTCA channel model can effectively eliminate the problem of multi-path delay estimation and reduce the signal subspace dimension of the channel correlation matrix, where the full-rank estimators using pilot subcarriers can be adopted, and consequently, improve the channel estimation performance.     

A reduced complexity channel estimation for OFDM systems withtransmit diversity in mobile wireless channels

A reduced complexity channel estimation for OFDM systems with transmit diversity is proposed by exploiting the correlation of the adjacent subchannel responses. The sizes of the matrix inverse and the FFTs required in the channel estimation at every OFDM data symbol are reduced by half of the existing method for OFDM systems with nonconstant modulus subcarrier symbols or constant modulus subcarrier symbols with some guard tones. The complexity reduction of half FFTs size and some matrix multiplications is still achieved for constant modulus subcarrier symbols with no guard tones. The price for the complexity reduction is a slight BER degradation and for the channels with small relative delay spreads, the BER performance of the reduced complexity method becomes quite comparable to the existing method. An alternative approach for the number of significant taps required in the channel estimation is described which achieves a comparable performance to the case with the known suitable number of significant taps. A simple modification which reduces the lost leakage of the nonsample-spaced channel paths is also proposed. This modification achieves a substantial performance improvement over the existing method without any added complexity     

Receiver structures for time-varying frequency-selective fadingchannels

Several receiver structures for linearly modulated signals are proposed for time-varying frequency-selective channels. Their channel estimators explicitly model the time variation of the channel taps via polynomials. These structures are constructed from the following building blocks: (i) sliding or fixed block channel estimators; (ii) maximum likelihood sequence detectors (MLSDs) or decision feedback equalizers (DFEs); and (iii) single or multiple passes. A sliding window channel estimator uses a window of received samples to estimate the channel taps within or at the end of the window. Every symbol period, the window of samples is slid along another symbol period, and a new estimate is calculated. A fixed block channel estimator uses all received samples to estimate the channel taps throughout the packet, all at once. A single pass receiver estimates the channel and detects data once only. A multipass receiver performs channel estimation and data detection repetitively. The effect of the training symbol positions on the performance of the block multipass approach is studied. The bit error rate (BER) performance of the MLSD structures is characterized through simulation and analysis. The proposed receivers offer a range of performance/complexity tradeoffs, but all are well suited to time-varying channels. In fast fading channels, as the signal-to-noise ratio (SNR) increases, they begin to significantly outperform the per-survivor processing-based MLSD receivers which employ the least mean-squares (LMS) algorithm for channel estimation     

一种改进的信道估计算法

文章在传统固定抽头系数信道估计的基础上,提出了一种改进的方法一活动抽头系数信道估计.这种信道估计,运用Akaike信息准则,寻找与实际信道最相符的最佳信道结构模式,而非固定的信道最恶劣条件下的模式结构.这样应用找到的最佳信道模式就可以减少均衡器的状态数目,节约平均处理过程,从而节省资源.并且在在系统误码性能上也有明显提高.     

Sub‐Nyquist rate ADC sampling‐based compressive channel estimation

To realize high‐speed communication, broadband transmission has become an indispensable technique in the next‐generation wireless communication systems. Broadband channel is often characterized by the sparse multipath channel model, and significant taps are widely separated in time, and thereby, a large delay spread exists. Accurate channel state information is required for coherent detection. Traditionally, accurate channel estimation can be achieved by sampling the received signal with large delay spread by analog‐to‐digital converter (ADC) at Nyquist rate and then estimate all of channel taps. However, as the transmission bandwidth increases, the demands of the Nyquist sampling rate already exceed the capabilities of current ADC. In addition, the high‐speed ADC is very expensive for ordinary wireless communication. In this paper, we present a novel receiver, which utilizes a sub‐Nyquist ADC that samples at much lower rate than the Nyquist one. On the basis of the sampling scheme, we propose a compressive channel estimation method using Dantzig selector algorithm. By comparing with the traditional least square channel estimation, our proposed method not only achieves robust channel estimation but also reduces the cost because low‐speed ADC is much cheaper than high‐speed one. Computer simulations confirm the effectiveness of our proposed method. Copyright © 2013 John Wiley & Sons, Ltd.