Blind estimation of a fractionally sampled FIR channel for OFDM transmission using residue polynomials

This paper introduces blind-channel estimation methods using residue polynomials for orthogonal-frequency-division-multiplexing (OFDM) transmission under the assumption that the channel is finite-impulse response (FIR). In terms of z transform, if the received signal is multiplied by the inverse of the transmitted signal, the resulting z transform renders the channel transfer function when additive noise is absent in the channel. For an FIR channel, samples of the recovered impulse response must be zero in the region of zeros of the channel impulse response. Based on this observation, the blind estimation problem is formulated as a solution of linear equations, treating the transmitted symbols as unknown variables. Polynomial residue arithmetic turns out to be very useful for deriving the linear equations. The proposed method is computationally more efficient than subspace methods that are applied for OFDM transmission systems. In addition, unlike subspace methods, the proposed method is deterministic and does not require estimation of the autocorrelation matrix of received signals, which is required in subspace methods.     

Subspace-based blind channel estimation for OFDM by exploiting virtual carriers

Reliable channel estimation is indispensable for orthogonal frequency-division multiplexing (OFDM) systems employing coherent detection and adaptive loading in order to achieve high data rate communications. Several options exist in practical OFDM systems-including training symbols, cyclic prefix, virtual carriers, pilot tones, and receiver diversity-to facilitate channel estimation. In this paper, a subspace blind channel estimation method based on exploiting the presence of virtual carriers is proposed for OFDM systems over a time-dispersive channel. The method can be applied to conventional OFDM systems with cyclic prefix as well as OFDM systems with no cyclic prefix. The reduction/elimination of cyclic prefix thereby provides the OFDM systems the potential to achieve higher channel utilization than most previously reported cyclic prefix based estimators. Sufficient channel identifiability condition is developed as well. Comparison with two other recently reported subspace methods is presented via computer simulations to support the effectiveness of the proposed method.     

MIMO-OFDM系统中信道盲估计与检测

针对MIMO-OFDM系统,提出了一种基于子空间的盲信道估计与检测方案,该算法将阵列信号处理的思想应用到MIMO-OFDM系统中,通过发送端信号的冗余编码,利用一种类ESPRIT算法进行盲信号检测和信道估计。仿真结果表明该算法的有效性及其信道盲估计方法的性能。     

Subspace Projection-based OFDM Channel Estimation

In this paper, we investigate the benefits of pre-processing received data by projection on the performance of channel estimation for orthogonal frequency division multiplexing (OFDM) systems. Projecting data onto its signal subspace will reduce the additive noise energy in the data. Least square (LS) estimation is a low-complex algorithm for training-based OFDM systems and the lower bound on the mean-square error of it is proportional to the noise variance. So, after the received data is pre-processed (projected onto its signal subspace), LS channel estimation on the pre-processed data will increase the performance of channel estimation. This method can also work in multiple-input and multiple-output (MIMO) case. Performance analysis and simulation results show that the proposed algorithm has a considerably smaller complexity than the linear minimum mean square error estimation while having almost the same performance.     

基于信号子空间的改进OFDM系统信道半盲估计

本文改进了一种基于信号子空间的OFDM系统半盲信道估计算法.该算法利用基于梯度变化的变遗忘因子递归最小二乘算法(GVFF-RLS)计算接收信号的自相关矩阵.通过同时对角化接收信号中的信息信号和噪声信号的全局协方差矩阵,推导出噪声信号子空间,无需对噪声信号的统计特性进行任何先验假定.本算法弥补了原始算法在慢衰落信道下收敛慢以及只限于加性白噪声的不足,实现了色噪声背景下高效半盲信道估计.仿真结果表明本文提出的算法具有良好的性能.     

OFDM系统信道盲估计的一种新算法

利用循环前缀（CP）引入的信息冗余，在利用接受信号的二阶统计特性实现正交频分复用（OFDM）系统信道盲估计的子空间算法基础上，采用矩阵变换的方法，改善信息序列的非周期相关函数，推导出信道估计的新算法。     

Fast blind channel estimation for space–time block coded MIMO–OFDM systems

Fast blind subspace channel estimation using circular property of the channel matrix is investigated for space–time block coded (STBC) multiple-input multiple-output orthogonal frequency division multiplexing (MIMO–OFDM) systems in this paper. The noise subspace computed from the correlation matrix of received signals requires a large number of symbols to converge in the subspace channel estimation. Using the circular property of the channel matrix, we propose both the cyclic repetition method (CRM) and the forward–backward method (FBM) to generate N times of equivalent signals for each STBC–OFDM symbol, respectively, where N is the size of FFT operation. With these equivalent symbols, the proposed CRM, FBM and CRM–FBM (CFBM) channel estimations can perform very well within a few OFDM symbols. The CRM, FBM and CFBM schemes are applicable to the CP-OFDM, ZP-OFDM and VC-OFDM systems, respectively. The identifiability of the subspace channel estimation is investigated that the channel matrix is determined up to two ambiguity matrices. Computer simulations demonstrate that the CRM-based, FBM-based and CFBM-based channel estimations have better performances than the conventional ones.     

Subspace-based blind and semi-blind channel estimation for OFDMsystems

This paper proposes a new blind channel estimation method for orthogonal frequency division multiplexing (OFDM) systems. The algorithm makes use of the redundancy introduced by the cyclic prefix to identify the channel based on a subspace approach. Thus, the proposed method does not require any modification of the transmitter and applies to most existing OFDM systems. Semi-blind procedures taking advantage of training data are also proposed. These can be training symbols or pilot tones, the latter being used for solving the intrinsic indetermination of blind channel estimation. Identifiability results are provided, showing that in the (theoretical) situation where channel zeros are located on subcarriers, the algorithm does not ensure uniqueness of the channel estimation, unless the full noise subspace is considered. Simulations comparing the proposed method with a decision-directed channel estimator finally illustrates the performance of the proposed algorithm     

子空间算法在OFDM信道时延估计中的应用

到达时延(TOA)和到达时延差(TDOA)定位算法是无线定位中应用最广泛的2种方法,TOA测量值的准确获取将影响定位的精确度。正交频分复用(OFDM)是实现无线多媒体通信的关键技术,利用OFDM信号的导频子载波所携带的信息,参考均匀线列阵的DOA估计过程,提出将MUSIC子空间法应用到OFDM信道的时延估计上。给出了OFDM符号内导频子载波分布的相关条件,对提出算法进行仿真实验,可以看出,导频子载波个数的增加和导频子载波间隔的扩大都可以提高估计精确度。     

MIMO—OFDM系统基于子空间的盲信道估计技术

MIMO-OFDM系统能在宽带无线信道中达到很高的速率。文章建立了MIMO-OFDM信道识别的条件并实现了基于子空间方法的盲信道估计技术。该方法将现存的在SISO-OFDM系统中的基于子空间的盲信道估计进行统一，并且推广到MIMO-OFDM系统中。特别是该方法可以获得信道的精确估计，且能快速收敛。仿真实验的结果显示了该方法的均方误差性能。     

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.     

快速的ZP-OFDM系统中的盲信道估计算法

基于子空间的盲信道估计因为其节约带宽和发射功率成为OFDM系统中比较热门的研究领域。但是,之前很多子空间算法有的收敛速度快,计算复杂度却高,有的用迭代算法跟踪子空间的特征结构,复杂度较低,但收敛速度却比较慢。提出了一种基于快速收敛的LMS-Newton算法的ZP-OFDM系统的信道估计方法,既提高了收敛速度,计算复杂度又不是很高。借助于子空间跟踪,该算法可以自适应地估计信道相关矩阵的噪声子空间,从而估计OFDM系统信道。仿真结果表明该算法可以改善信道估计的性能。     

Sampling Frequency Offset Estimation for Pilot-Aided OFDM Systems in Mobile Environment

In orthogonal frequency division multiplexing (OFDM) systems, most of the conventional sampling frequency offset (SFO) estimation methods work under the assumption of time-invariant or slow time-variant channels. In mobile environment, the time-variant channel significantly degrades the accuracy of SFO estimation. To solve the problem, we first analyze the properties of time-variant channels. If terminal moves within some tens of the wavelength of radio frequency (RF) signal, channel path delay almost remains unchanged. For most practical OFDM systems, our analysis indicates that channel path delay can be regarded as unchanged during the interval of some tens of OFDM symbols in time-variant channels. Based on the analysis, we propose a novel SFO estimation method for pilot-aided OFDM systems. Different from the conventional methods, the proposed method estimates SFO by detecting the variation of the symbol timing error caused by SFO. The detection is finished by implementing correlation between the channel impulse responses (CIRs) estimated by different OFDM symbols. Performance of the proposed method is simulated and compared with that of two conventional post-FFT methods. Numerical results show that, the proposed SFO estimation method performs better than the conventional methods not only in time-variant channels, but also at low SNRs and large residual carrier frequency offsets (CFOs).     

基于导频信号的OFDM通信系统信道估计与跟踪

讨论了在正交频分复用(OFDM)通信系统中,基于导频信号,采用投影逼近子空间(PAST)算法实现信道的跟踪估计,在快速变化的信道中,信道阶数自动跟踪,与传统的信道估计方法相比,信道估计精度提高,均方误差减小.通过计算机模拟仿真,验证了信道估计的跟踪性能得到了改善.     

Semiblind Channel Estimation and Signal Detection for OFDM System with Receiver Diversity

In this paper, we address the problem of channel estimation and signal detection for orthogonal frequency division multiplexing (OFDM) system with multiple receive antennas. The received signal can be denoted as a trilinear model, and then a trilinear decomposition-based channel estimation and signal detection algorithm is proposed. Scalar ambiguity which is inherent in the blind algorithms can be easily resolved by insertion fewer pilots in the proposed algorithm. Compared with conventional subspace approaches, the proposed algorithm has improved estimation performance, and the signal detection performance of the proposed algorithm is very close to non-blind minimum mean square error (MMSE) receiver. Furthermore, our proposed algorithm works well in the presence/absence of virtual carriers, and it does not require knowledge of statistical characteristics. Simulation results illustrate performance of the algorithm.     

基于子空间分解的OFDM信道盲辨识

该文提出一种基于子空间分解的正交频分复用(OFDM)信道的盲辨识算法,将OFDM信号等效为单输入多输出的过采样信号,采用过采样信号的循环稳态特性和子空间分解方法估计信道参数,算法不需要任何训练序列和周期性的引导信号,实现了0FDM信道的盲辨识。对于宽带OFDM移动通信系统,通常子信道数较大,信道响应持续时间短于0FDM符号周期,因此,可以将整个系统分为若干个子系统,各子系统分别进行信道辨识,能有效地降低信道估算的复杂性。     

限幅OFDM系统中的判决辅助信道估计

在正交频分复用(OFDM)系统中，对基带时域信号限幅是通常采用的一种降低信号峰均比的方法，但是由限幅产生的非线性干扰使系统的信道估计和信号检测性能降低。本文针对OFDM系统的频域插值信道估计方案，分析了限幅对信道估计性能的影响，提出一种利用判决的信号辅助信道估计的方法，并分析了该方法为信道估计所能提供的最大信干比增益。理论分析和仿真结果表明这种方法能够提高信道估计的精度，从而提高信号检测的性能，降低接收机的误符号率。     

基于OFDM信号的外辐射源雷达杂波信道估计

基于正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)信号调制特性的外辐射源雷达杂波信道状态信息估计方法,针对OFDM外辐射源雷达探测存在的问题,提出了基于信号特性的处理方法。针对该体制雷达中纯净的直达波信号获取问题,提出基于模糊函数的方法提取导频的周期信息,从而得到导频的位置信息,然后,利用导频信息得到杂波信道脉冲响应信息估计。相比常规的处理方法,文中方法能够在参考信号包含多径时得到正确的杂波信道状态信息。     

基于信道分段平滑的外辐射源雷达非平稳杂波抑制方法

复杂电磁环境下,外辐射源雷达中多径杂波可能具备非平稳的跳变特性。该文针对这种跳变型非平稳杂波,结合辐射源信号的正交频分复用(OFDM)调制特性,提出一种基于信道分段平滑的杂波抑制方法。首先建立了跳变杂波的时域信号模型,然后结合OFDM信号结构将其变换到子载波域,接着在子载波域对各OFDM符号进行信道估计与分段平滑,最后利用该信道平滑值和对应段的参考信号抑制非平稳杂波。仿真和实测数据表明,该文方法能够有效抑制跳变型的非平稳杂波。     

Robust subspace blind channel estimation for cyclic prefixed MIMO ODFM systems: algorithm, identifiability and performance analysis

A novel subspace (SS) based blind channel estimation method for multi-input, multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems is proposed in this work. With an appropriate re-modulation on the received signal blocks, the SS method can be effectively applied to the cyclic prefix (CP) based MIMO-OFDM system when the number of the receive antennas is no less than the number of transmit antennas. These features show great compatibility with the coming fourth generation (4G) wireless communication standards as well as most existing single-input single-output (SISO) OFDM standards, thus allow the proposed algorithm to be conveniently integrated into practical applications. Compared with the traditional SS method, the proposed algorithm exhibits many advantages such as robustness to channel order over-estimation, capability of guaranteeing the channel identifiability etc. Analytical expressions for the mean-square error (MSE) and the approximated Cramer-Rao bound (ACRB) of the proposed algorithm are derived in closed forms. Various numerical examples are conducted to corroborate the proposed studies.