Channel estimation for OFDM transmission in multipath fadingchannels based on parametric channel modeling

We present an improved channel estimation algorithm for orthogonal frequency-division multiplexing mobile communication systems using pilot subcarriers. This algorithm is based on a parametric channel model where the channel frequency response is estimated using an L-path channel model. In the algorithm, we employ the ESPRIT (estimation of signal parameters by rotational invariance techniques) method to do the initial multipath time delays acquisition and propose an interpath interference cancellation delay locked loop to track the channel multipath time delays. With the multipath time delays information, a minimum mean square error estimator is derived to estimate the channel frequency response. It is demonstrated that the use of the parametric channel model can effectively reduce the signal subspace dimension of the channel correlation matrix for the sparse multipath fading channels and, consequently, improve the channel estimation performance     

OFDM channel estimation in the presence of interference

We develop a frequency-domain channel estimation algorithm for single-user multiantenna orthogonal frequency division multiplexing (OFDM) wireless systems in the presence of synchronous interference. In this case, the synchronous interferer's signal on each OFDM subcarrier is correlated in space with a rank one spatial covariance matrix. In addition, the interferer's spatial covariance matrix is correlated in frequency based on the delay spread of the interferer's channel. To reduce the number of unknown parameters we develop a structured covariance model that accounts for the structure resulting from the synchronous interference. To further reduce the number of unknown parameters, we model the covariance matrix using a priori known set of frequency-dependent functions of joint (global) parameters. We estimate the interference covariance parameters using a residual method of moments (RMM) estimator and the channel parameters by maximum likelihood (ML) estimation. Since our RMM estimates are invariant to the mean, this approach yields simple noniterative estimates of the covariance parameters while having optimal statistical efficiency. Hence, our algorithm outperforms existing channel estimators that do not account for the interference, and at the same time requires smaller number of pilots than the MANOVA method and thus has smaller overhead. Numerical results illustrate the applicability of the proposed algorithm.     

一种新的快衰落信道频域跟踪算法

该文研究了第三代移动通信系统中用户移动速度在150km/h以上时,无线信道的快衰落特性,并且在3GPP系统的协议框架下提出了一种新的基于频域的信道跟踪方法(FBP),利用快衰落信道频域上的相对稳定性,解决了由于信道参数变化的速度超过自适应算法收敛速度,而造成的在时域上无法进行信道跟踪的问题,文章给出了该算法的模拟结果,并与另一种对衰落信道的参数进行基于小波的信道跟踪算法(WBP)进行了比较,该文提出的算法具有更好的性能和更低的算法复杂度。     

一种改进的ISFA信道估计算法

设计了一种基于符号内频域平均(ISFA)的信道估计算法,用于偏振复用光正交频分复用(PDM-O-OFDM)系统的信道估计和传输信道色散损伤的均衡。算法采用凯撒窗函数对基于导频的ISFA算法进行改进,提高了信道估计后处理的精度,改善了长距离PDM-O-OFDM系统的误码率(BER)和光信噪比(OSNR)性能。通过仿真试验,确定了算法的相关参数,分析了算法对长距离系统中色散损伤的均衡性能。仿真结果表明,改进算法对于传输距离超过700km系统的均衡效果优于原算法,其中900km处的OSNR代价比原算法低0.35dB。     

基于二维DCT的TD-LTE系统信道估计方法

在TD-LTE（Time Division-Long Term Evolution）系统中,由于高速移动产生多普勒频偏,使传统的基于DFT（Discrete Fourier Transform）插值信道估计算法性能损失严重。为了解决上述问题,本文提出一种利用TD-LTE系统导频模式的二维离散余弦变换（2D-DCT）信道估计算法,并给出了详细的推导。仿真结果表明,该方法的性能优于2D-DFT算法,可以很好的接近于2D维纳滤波估计算法。     

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。     

A low complexity pilot aided channel estimation method for WCDMA communication systems

This letter deals with the performance evaluation of a pilot aided method for estimating channel parameters in wideband code division multiple access (WCDMA) communication systems. Unlike previous approaches, a successive interference cancellation algorithm is used to reduce multipath and multiuser interference caused by pilot signal replicas on the channel parameter estimation, and on the detection of the information bearing signals. Comparisons with the ideal case of perfect knowledge of the channel parameters and the classical channel parameter estimation algorithm have highlighted the good performance of the proposed approach.     

Parametric SNR Estimation Based on Auto-Regressive Model in AWGN Channels

Signal-to-noise ratio（SNR）estimation for signal which can be modeled by Auto-regressive（AR）process is studied in this paper.First,the conventional frequency domain method is introduced to estimate the SNR for the received signal in additive white Gauss noise（AWGN）channel.Then a parametric SNR estimation algorithm is proposed by taking advantage of the AR model information of the received signal.The simulation results show that the proposed parametric method has better performance than the conventional frequency doma in method in case of AWGN channel.     

On channel parameter estimation in a space-time bit-interleaved-coded modulation system for multipath DS-CDMA uplink with receive diversity

In this paper, we consider iterative space-time multiuser detection and channel parameter estimation in a bit-interleaved coded modulation scheme for asynchronous direct-sequence code division multiple access (DS-CDMA) transmission over frequency selective, slowly fading channels. Accurate estimation of the channel parameters is critical as it has great impact on the overall BER performance. We present an iterative space-time multiuser (STMU) turbo detection and estimation scheme, based on space alternating generalized expectation maximization (SAGE) algorithm. This algorithm operates on the coded symbols by exchanging soft information between the detector and the estimator. We show through computer simulations that the proposed low complexity STMU receiver considerably outperforms conventional estimation schemes and achieves excellent performance, both in terms of BER and estimation error variance. Finally, we will consider different mapping strategies and investigate their impact on the performance and complexity of the estimator.     

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     

Construction of block orthogonal golay sequences and application to channel estimation of mimo-ofdm systems

In this paper, we construct a family of block orthogonal Golay sequences that have low peak-to-mean envelope power ratio (PMEPR) as well as block wise orthogonal properties. We then present an application of the sequences to channel estimation of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. We compare the performance of the proposed algorithm with that of a frequency division multiplexing (FDM) piloting algorithm, and investigate the effect of co-channel interference (CCI) on the channel estimation performance.     

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。     

Effects of imperfect channel sensing and estimation on the performance of cognitive radio systems

In realistic scenarios of cognitive radio (CR) systems, imperfect channel sensing may occur due to false alarms and miss detections. Channel estimation between the secondary user transmitter and another secondary user receiver is another challenge in CR systems, especially for frequency‐selective fading channels. In this context, this paper presents a study of the effects of imperfect channel sensing and channel estimation on the performance of CR systems. In particular, different methods of channel estimation are analyzed under channel sensing imperfections. Initially, a CR system model with channel sensing errors is described. Then, the expectation maximization (EM) algorithm is implemented in order to learn the channel fading coefficients. By exploiting the pilot symbols and the detected symbols at the secondary user receiver, we can estimate the channel coefficients. We further compare the proposed EM estimation algorithm with different estimation algorithms such as the least squares (LS) and linear minimum mean square error (LMMSE). The expressions of channel estimates and mean squared errors (MSE) are determined, and their dependencies on channel sensing uncertainty are investigated. Finally, to reduce the complexity of EM algorithm, a sub‐optimal algorithm is also proposed. The obtained results show that the proposed sub‐optimal algorithm provides a comparable bit error rate (BER) performance with that of the optimal one yet with less computational complexity.     

BLIND CHANNEL ESTIMATION OF SPACE-TIME FREQUENCY-SHIFT KEYING

The decoupled coherent Maximum Likelihood （ML） detection algorithm presented in this letter can sharply reduce the complexity of the receiver as well as provide better error performance under the precondition that channel should be estimated first. Considering the bandwidth inefficiency of Frequency Shift Keying （FSK）, the acquisition of channel state information through training sequences will further decrease the transmission efficiency. This letter presents a blind channel estimation algorithm based on noise subspace theory which can acquire channel information without any training symbols. The simulation shows that the algorithm brings about fewer channel estimation errors while the frequency efficiency can be increased.     

基于网格搜索的同步损伤和信道联合估计算法

为了实现多输入多输出(MIMO)正交频分复用(OFDM)系统中同步损伤和信道的联合估计,提出了一种基于网格搜索的联合估计算法。首先通过构建起一个以反映同步损伤和信道响应影响的系统模型,然后将各损伤参数估计的多维优化问题简化为二维网格和一维网格搜索,从而实现对载波频率偏移、采样频率偏移和符号定时误差的联合估计;数值仿真结果表明,本文提出的联合估计算法相比于非联合估计算法具有更好的估计性能。     

基于总体最小二乘准则的OFDM系统时变信道估计

信道估计的准确程度直接影响正交频分复用系统的性能。为了提高时变信道估计算法的精度,基于总体最小二乘准则( TLS)提出了一种时变信道的估计方法。该方法用线性模型对时变信道进行建模,不仅考虑了信道噪声,同时也兼顾了模型误差。该方法能较好地跟踪信道的变化,显著消除模型误差。仿真结果表明所提算法的均方误差介于最小二乘算法与最小均方误差算法之间,在不同归一化多普勒频移下,该算法具有较好的稳健性。     

Side-information-dependent correlation channel estimation in hash-based distributed video coding

In the context of low-cost video encoding, distributed video coding (DVC) has recently emerged as a potential candidate for uplink-oriented applications. This paper builds on a concept of correlation channel (CC) modeling, which expresses the correlation noise as being statistically dependent on the side information (SI). Compared with classical side-information-independent (SII) noise modeling adopted in current DVC solutions, it is theoretically proven that side-information-dependent (SID) modeling improves the Wyner-Ziv coding performance. Anchored in this finding, this paper proposes a novel algorithm for online estimation of the SID CC parameters based on already decoded information. The proposed algorithm enables bit-plane-by-bit-plane successive refinement of the channel estimation leading to progressively improved accuracy. Additionally, the proposed algorithm is included in a novel DVC architecture that employs a competitive hash-based motion estimation technique to generate high-quality SI at the decoder. Experimental results corroborate our theoretical gains and validate the accuracy of the channel estimation algorithm. The performance assessment of the proposed architecture shows remarkable and consistent coding gains over a germane group of state-of-the-art distributed and standard video codecs, even under strenuous conditions, i.e., large groups of pictures and highly irregular motion content.     

Frequency-selective multiple-input multiple-output channel estimation with transmitter non-linearities

The authors propose an algorithm based on the knowledge of training sequences to obtain an asymptotically unbiased estimator of non-linear multiple-input multiple-output (MIMO) channels, which involves the radio frequency front-end non-linearity and linear frequency selective MIMO channels. Although the impact of non-linearity in the transmitter side has been widely studied, most work on the channel estimation assumes linear channel models and ignores the non-linear effects. In this study, we develop a nonlinear channel estimator that can simultaneously estimate the linear MIMO channel model and non-linearity of the transmitter is developed. With these two sets of parameters, the non-linear channel model can be fully described. This channel estimation algorithm is implemented over an empirical MIMO channel model using an orthogonal frequency division multiplexing system.     

Maximum-likelihood-based multipath channel estimation forcode-division multiple-access systems

The problem of estimating the channel parameters of a new user in a multiuser code-division multiple-access (CDMA) communication system is addressed. It is assumed that the new user transmits training data over a slowly fading multipath channel. The proposed algorithm is based on maximum-likelihood estimation of the channel parameters. First, an asymptotic expression for the likelihood function of channel parameters is derived and a re-parametrization of this likelihood function is proposed. In this re-parametrization, the channel parameters are combined into a discrete time channel filter of symbol period length. Then, expectation-maximization algorithm and alternating projection algorithm-based techniques are considered to extract channel parameters from the estimated discrete channel filter, to maximize the derived asymptotic likelihood function. The performance of the proposed algorithms is evaluated through simulation studies. In addition, the proposed algorithms are compared to previously suggested subspace techniques for multipath channel estimation