Semiblind Channel Estimation for MIMO Single Carrier With Frequency-Domain Equalization Systems

We propose a semiblind channel-estimation method for multiple-input multiple-output (MIMO) single carrier with frequency-domain equalization systems. By taking advantage of periodic precoding and the block circulant channel model after cyclic prefix removal, we obtain the channel-product matrices by solving a series of decoupled linear systems, which is gained from the covariance matrix of the received data. Then, the channel-impulse-response matrix is obtained by computing the positive eigenvalues and eigenvectors of a Hermitian matrix formed from the channel-product matrices. We also propose an optimal design of the precoding sequence, which minimizes the noise effect and numerical error in covariance matrix estimation, and discuss the impact of the optimal sequence on channel equalization. With the proposed framework, the method is shown to be robust with respect to channel-order overestimation, and the identifiability condition is simply that the channel-impulse-response matrix has full column rank. Due to the identifiability condition, the method is applicable to MIMO channels with more transmitters or more receivers. Simulations are used to demonstrate the performance of the proposed method.      

MIMO Receiver Using Reduced Complexity Sequence Estimation With Channel Estimation and Tracking

A sequence-based multiple-input–multiple-output receiver incorporating channel estimation and tracking for a frequency selective fading environment is developed. It employs near-maximum likelihood sequence estimation using the partitioned Viterbi algorithm and offers linearly increasing complexity with the number of transmit antennas. The receiver implements channel estimation and tracking using a vector-polynomial-based generalized recursive least squares algorithm. The resulting integrated receiver can operate in a continuously time-varying Rayleigh or Rician fading environment. Simulation results show that it offers a good tradeoff between complexity and performance. Further complexity reduction can be achieved using tentative decisions as reference signals to the estimator and a reduced complexity form of the estimator.      

基于多项式内插的MIMO时间-频率双选择性信道的信道估计

数据的高速率传输以及终端的高速移动,导致无线通信信道具有时间选择性与频率选择性两个特征。该文主要研究了数据分组传输方式下,基于导频符号辅助调制(PSAM)的多输入多输出(MIMO)时间-频率双选择性信道的信道估计问题。首先,将时间-频率双选择性MIMO信道,建模为一个随时间变化的多项式内插信道模型;然后,根据信道Doppler衰落速率、多项式模型中的误差项,确定出模型的阶数以及整个数据块的长度;最后,基于该多项式内插信道模型,提出了采用PSAM的MIMO双选择性信道估计方法。实验结果表明该算法在时间-频率双选择性衰落信道下具有较好的性能。     

基于隐训练序列的MIMO通信系统信道估计与跟踪

针对MIMO通信系统的信道估计与跟踪问题,提出了一种基于隐训练序列(ITS)的信道估计算法,分析了该算法的均方误差性能,给出了训练序列的优化方案.仿真表明,该算法与传统的最小二乘信道估计算法、预编码隐训练序列算法相比,具有估计精度高、计算量低、易于优化训练序列等特点,且算法不受接收端存在直流偏移的影响,其自适应结构能够很好地实现对快时变通信信道的跟踪,对解决电子战中快时变通信信道的捕获和跟踪问题具有一定的指导意义和应用价值.     

Bounds on SIMO and MIMO Channel Estimation and Equalization with Side Information

Constrained Cramér-Rao bounds are developed for convolutive multi-input multi-output (MIMO) channel and source estimation in additive Gaussian noise. Properties of the MIMO Fisher information matrix (FIM) are studied, and we develop the maximum rank of the unconstrained FIM and provide necessary conditions for the FIM to achieve full rank. Equality constraints on channel and signal parameters provide a means to study the potential value of side information, such as training symbols (semi-blind case), constant modulus (CM) sources, or known channels. Nonredundant constraints may be combined in an arbitrary fashion, so that side information may be different for different sources. The bounds are useful for evaluating the performance of SIMO and MIMO channel estimation and equalization algorithms. We present examples using the constant modulus blind equalization algorithm. The constrained bounds are also useful for evaluating the relative value of different types of side information, and we present examples comparing semi-blind, constant modulus, and known channel constraints. While the examples presented are primarily in the communications context, the CRB framework applies generally to convolutive source separation problems.     

Application of Sequential Estimation Algorithm Based on Branch Metric to Frequency-Selective Channel Equalization

In this work, a sequential estimation algorithm based on branch metric is used as channel equalizer to combat intersymbol interference in frequency-selective wireless communication channels. The bit error rate (BER) and computational complexity of the algorithm are compared with those of the maximum likelihood sequence estimation (MLSE), the recursive least squares (RLS) algorithm, the Fano sequential algorithm, the stack sequential algorithm, list-type MAP equalizer, soft-output sequential algorithm (SOSA) and maximum-likelihood soft-decision sequential decoding algorithm (MLSDA). The BER results have shown that whilst the sequential estimation algorithm has a close performance to the MLSE using the Viterbi algorithm, its performance is better than the other algorithms. Beside, the sequential estimation algorithm is the best in terms of computational complexity among the algorithms mentioned above, so it performs the channel equalization faster. Especially in M-ary modulated systems, the equalization speed of the algorithm increases exponentially when compared to those of the other algorithms.     

Improved Frequency Domain Channel Estimation and Equalization for MIMO Wireless Communications

This paper introduces an improved frequency domain channel estimation method based on interpolation vectors for single carrier frequency domain equalization (SC-FDE) with the multiple-input multiple-output (MIMO) scheme. The proposed algorithm is derived by employing the least squares (LS) criterion, and a specified application for the wide sense stationary uncorrelated scattering (WSSUS) Rayleigh fading channel is presented. The channel frequency domain responses estimated at two adjacent pilot blocks are used to track the time-variant channel information, which can effectively improve the accuracy of channel estimation without significantly increasing complexity. Maximum mean square error (MMSE) frequency domain equalization based on the estimated channel is employed in the receiver to recover transmitted signals. This paper also investigates a training sequence design method for multiple transmit antennas and a noise variance estimation method. Numerical simulation results show that the proposed methods can perform very well for fading channels with long multipath delay and high Doppler spread.     

基于导频和多项式模型的信道估计

本文提出一种基于导频辅助、多项式近似和信号重建的信道估计通用方法,适用于高速移动环境.假定无线信道响应具有多项式特性,用两个或多个时隙的导频符号,估计出该时间段内任意符号时刻上的信道响应值.用仿真方法研究了WCDMA上行链路性能与移动台速度的关系、最佳多项式阶数和最佳时隙数,并与WMSA方法进行了比较.     

Tracking Performance of Least Squares MIMO Channel Estimation Algorithm

In this paper, the tracking performance analysis of the least squares (LS) multiple-input multiple-output (MIMO) channel estimation and tracking algorithm is presented. MIMO channel estimation is a novel application of the LS algorithm that presents near-optimum performance by Karami and Shiva in 2003 and 2006. In this paper, the mean square error (MSE) of tracking of the LS MIMO channel estimator algorithm is derived as a closed-form function of the Doppler shift, forgetting factor, channel rank, and the length of training sequences. In the analysis, all training symbols are considered as randomly generated equal-power vectors on the unit circle, or in other words, phase-shift keying (PSK) signaling. By evaluating this function, some insights into the tracking behavior of the LS MIMO channel estimator are achieved. Then, the calculated tracking error is compared with the tracking error derived from Monte Carlo simulation for quaternary-PSK-based training signals to verify the validation of the presented analysis. Finally, the optimum forgetting factor is derived to minimize the error function, and it is shown that the optimum forgetting factor is highly dependent on the training length, Doppler shift, and E_b/N_o. Also, it is concluded that in low E_b/N_o values, the number of transmitter antennas has negligible effect on the optimal value of the forgetting factor.     

An Approach to Nonirreducible MIMO FIR Channel Equalization

It is known that a nonirreducible multiple-input-multiple-output finite-impulse-response channel driven by colored signals that are mutually uncorrelated and of sufficiently diverse power spectra can be identified blindly by exploiting only the second-order statistics of the measured data. In this brief, we propose an approach to dealing with the equalization of a nonirreducible channel, provided that the estimate of the channel matrix is available. Both zero-forcing and minimum-mean-square-error equalizers are developed to perform the channel equalization. The effectiveness of the approach and equalizers is demonstrated by simulation examples.     

一种新的基于参数信道模型的MIMO信道估计算法

针对频率选择性块衰落MIMO信道,该文提出一种改进的基于参数信道模型的信道估计方法。该方法首先通过修正后的TST-MUSIC算法估计多径的传播时延和角度。由时延和角度信息,得到一种基于参数信道模型的信道估计方法。仿真结果表明此种方法可以有效地减少参数估计的维数,其性能要远远优于非参数的最小二乘估计器。     

基于MCoSaMP算法的MIMO稀疏信道估计

针对单载波多输入多输出(Multiple Input Multiple Output,MIMO)系统中的稀疏信道估计问题,基于压缩传感(Compressed Sensing,CS)理论,提出了一种改进的压缩采样匹配追踪(Modified Compressive Sampling Matching Pursuit,MCoSaMP)算法.新算法在现有的压缩采样匹配追踪算法的基础上,通过前一步迭代的残差设计了一种自适应加权因子,利用该加权因子进行加权最小二乘估计,逐步减小了异常样本对当前估计的影响.仿真结果表明,在使用相同长度的训练序列时,新算法与现有的基于压缩采样匹配追踪的估计算法相比,在估计精度上有明显提高.     

Space–Time-Coded MIMO ZP-OFDM Systems: Semiblind Channel Estimation and Equalization

The space–time-block-code (STBC) multiple-input–multiple-output (MIMO) zero-padding orthogonal frequency-division multiplexing (ZP-OFDM) has been widely investigated in recent years. It provides a good performance for the multiuser scenario with a small number of pilots. However, it would fail in the face of complex symmetric signals. In this paper, novel channel estimation and equalization for complex input signals are investigated. With the Alamouti-like STBC scheme, the channel impulse responses of the space–time-coded MIMO ZP-OFDM system are shown to be identifiable up to two ambiguity matrices by subspace channel estimation. The frequency domain minimum mean-square error (MMSE) equalizer is then employed to detect the OFDM symbols. Furthermore, we propose a forward–backward averaging technique to enhance the performances of blind channel estimation. The weight analysis for the MMSE equalizer is also conducted to reduce the complexity of system design. Computer simulations demonstrate the effectiveness and correctness of channel estimation and weight analysis for the space–time-coded MIMO ZP-OFDM systems.      

OFDM联合信道估计与均衡技术研究

OFDM系统在时变信道中会受到子载波间干扰,单独进行信道估计和信号检测的策略对于提高接收机的抗干扰能力有限,将信道估计和信号检测统一考虑则可更有效地抵抗子载波间干扰。针对此问题,基于迭代SAGE算法提出了一种新的联合信道估计与符号检测算法,为了减低算法的复杂度,引入BEM信道建模方法。仿真评估了BEM算法的归一化均方误差性能,验证了BEM建模的有效性,显示该算法的误码率优于基于BEM算法的线性均衡检测算法和基于MMSE的干扰对消算法,而且该算法只通过少数几次迭代便可达到收敛域,较好地克服了子载波间干扰的问题。     

Blind MIMO Channel Estimation Based on Modulation-Induced Two-Cycle Cyclostationarity

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An Information Geometric Approach to ML Estimation With Incomplete Data: Application to Semiblind MIMO Channel Identification

In this paper, we cast the stochastic maximum-likelihood estimation of parameters with incomplete data in an information geometric framework. In this vein, we develop the information geometric identification (IGID) algorithm. The algorithm consists of iterative alternating projections on two sets of probability distributions (PDs); i.e., likelihood PDs and data empirical distributions. A Gaussian assumption on the source distribution permits a closed-form low-complexity solution for these projections. The method is applicable to a wide range of problems; however, in this paper, the emphasis is on semiblind identification of unknown parameters in a multiple-input multiple-output (MIMO) communications system. It is shown by simulations that the performance of the algorithm [in terms of both estimation error and bit-error rate (BER)] is similar to that of the expectation-maximization (EM)-based algorithm proposed previously by Aldana et al., but with a substantial improvement in computational speed, especially for large constellations.     

A MIMO Channel Prediction Scheme Based on Multi-Task Learning

Wireless Personal Communications - This paper proposes a multi-input multi-output (MIMO) channel prediction scheme using multi-task learning algorithm. Based on the spatially correlated MIMO...     

基于多项式拟合的二维OFDM信道估计算法

该文提出了一种内插导频的二维信道估计算法,用于无线移动信道下的正交频分复用(OFDM)系统。该算法能够适用于矩形内插的导频信号内插方式,相比于梳状内插的导频信号内插方式,矩形内插具有更高的数据传输效率。与已有线性最小均方差(LMMSE)信道估计方法相比,该算法简单并且不需要预先知道信道相关矩阵以及信噪比等信道信息。仿真结果表明,在各种的衰落环境下,该算法都有良好的性能。     

Frequency-Domain Channel Estimation and Equalization for Continuous-Phase Modulations With Superimposed Pilot Sequences

This paper proposes a new frequency-domain channel-estimation and equalization method for continuous-phase modulation (CPM) block transmissions with superimposed pilot signals. Our method provides spectral and power-efficient broadband CPM wireless communications with less complexity than previous methods. The proposed frequency-domain channel estimation uses the superimposed pilot sequence as a reference signal to reduce the throughput loss caused by traditionally multiplexed pilots. The proposed CPM frequency-domain decision feedback equalizer (DFE) eliminates the complexity overhead of conventional decomposition-based CPM receivers.      

MC-CDMA系统基于子空间跟踪的导频辅助信道估计

基于导频辅助的MC-CDMA系统信道估计方法通过在确定的时频位置发送已知的导频符号来获取信道参数,通常包括导频位置的最小二乘估计和内插滤波两步。为了提高导频位置信道频域特性的估计精度,使得后续内插滤波的精度相应得到提高,本文利用基于Givens旋转的子空间跟踪方法构成了对信道的时变参数的估计和跟踪,得到了较为准确导频信道估计。仿真表明,我们给出的基于子空间跟踪的信道估计方法具有更好的稳定性和更高的估计精度。