使用接收分集的确定性OFDM盲信道估计算法

本文针对无循环前缀的OFDM系统研究了非数据辅助的信道估计方法.借助于2个接收天线实现的信道分集,提出了一个确定性信道盲估计算法,并给出了信道可辨识性条件.该算法使用1个OFDM块便可在一个标量模糊因子的意义上确定信道冲激响应.算法计算量小,而且对输入信号的星座和统计特性没有约束.仿真结果证实了算法的有效性.     

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     

一种OFDM系统同步参数盲估计方法

首先提出一种扩大周期平稳信号循环周期的方法，然后在此基础上提出一种基于信号周期平稳特性的盲同步参数快速估计算法，最后通过分析算法获得一种可以估计非整数倍样点周期时延和扩大频偏估计范围的方法，从而实现整个OFDM基带带宽范围内的频偏估计。理论分析和仿真结果表明，该算法仅用很少的OFDM符号就可以实现同步参数的估计、有好的抗噪特性、衰落信道适应性和高的估计精度。     

基于电力线信道的OFDM盲同步算法

在Takahashi提出的盲同步算法的基础上,提出了一种正交频分复用（OFDM）多符号联合的差分盲同步算法。同Takahashi的算法一样,该算法利用OFDM符号的循环前缀内不被多径时延扩展所影响的那部分码元提取定时信息,但是为了避免电力线信道中随机的脉冲噪声对符号同步产生的影响,在每个定时时刻,取差值的前后移动平均,并采用多个OFDM符号的联合,以增强同步效果。仿真结果表明,在第一径为最强径或是非最强径的电力线多径衰落信道中,该算法取得了更好的符号同步性能。     

基于电力线信道的OFDM盲同步算法

在Takahashi提出的盲同步算法的基础上,提出了一种OFDM多符号联合的差分盲同步算法。同Takahashi的算法一样,该算法利用OFDM符号的循环前缀内不被多径时延扩展所影响的那部分码元提取定时信息,但是为了避免电力线信道中随机的脉冲噪声对符号同步产生的影响,在每个定时时刻,取差值的前后移动平均,并采用多个OFDM符号的联合,以增强同步效果。仿真结果表明,在第一径为最强径或是非最强径的电力线多径衰落信道中,该算法取得了很好的符号同步效果。     

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。     

一种基于OFDM信号周期平稳特性的系统时延和频偏的盲估计算法

该文首先提出一种基于信号周期平稳特性的OFDM系统时延和频偏的盲估计算法,然后分析算法,获得一种可以估计非整数倍样点周期的时延和扩大频偏估计范围,实现整个OFDM系统带宽范围内的频偏估计的方法,并指出本算法可以在信道未知的情况下获得好的估计性能,最后给出相应的仿真结果。理论分析和仿真结果表明,本算法有很好的抗噪特性、强的变化信道适应性,与同类方法比较,具有更高的估计精度、估计非整数倍样点周期时延和扩大频偏估计范围的能力。     

OFDM中基于有限字符集特性的半盲信道估计

由于基于有限字符集特性的盲估计方法最短距离(MD)计算量大、收敛速度慢、消耗时间长,而修正后的MMD方法,计算量下降的同时精度也降低了很多,提出了一种基于有限字符集特性的半盲估计方法。该方法通过导频结合有限字符集特性,利用最小距离准则快速辨识出所有子载波上频率响应的相位。仿真结果表明,该算法的信道估计性能优于修改后的最小距离(MMD)算法,与MD相等,而计算复杂度大大低于MD和MMD算法。     

Joint channel and phase noise estimation in OFDM systems at very high speeds

In this paper, the problem of joint phase noise and channel estimation for OFDM systems over a fast time-varying frequency-selective channel is explored. Each channel tap time-variation within one OFDM symbol is approximated by a Basis Expansion Model (BEM). Joint estimation is performed on multiple OFDM symbols via the Extended Kalman Filtering in order to exploit the time-correlation of the parameters. The data symbols are estimated by means of an iterative pilot-based algorithm. It is shown that, with only 2 iterations, our algorithm outperforms the conventional one, and the performance approaches that of the ideal case for which the channel response and phase noise are known.     

Blind Channel Estimation for OFDM Systems via a Generalized Precoding

In this paper, we consider the problem of blind channel estimation for single-input-single-output (SISO) orthogonal frequency-division multiplexing (OFDM) system via second-order statistics only. Based on the assumption that the transmitted symbols are independent and identically distributed, we develop a simple blind channel estimation technique for OFDM systems by utilizing a generalized linear nonredundant block precoding. Instead of using partial information from the signal covariance matrix, as done in previous works where a specific precoder is designed and only one column of the signal covariance matrix is exploited, our work jointly considers all the information contained in the signal covariance matrix. Compared to the popular subspace-based blind channel estimation methods, the proposed algorithm is much more computationally efficient. A design criterion of the precoders by which the performance can be improved is provided, and the closed-form stochastic Crameacuter-Rao bound is derived. The numerical results clearly show the effectiveness of our proposed algorithm, as well as its improvement over the existing techniques     

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.     

一种OFDM系统中的盲信道估计算法

该文利用OFDM系统传输的信息符号为有限字符集和各子载波的相互独立特性,提出了用伪导频符号(PPS)进行信道的盲估计算法。与用于做信道估计的导频符号不同,PPS传输的是有用的数据,因此提高了系统的带宽利用率,PPS的平均功率增加3dB或6dB可有效抑制信道的加性高斯噪声。对信道盲估计的均方误差(MSE)和由此算法获得的信道的状态信息对无编码的OFDM系统进行解调的误比特率进行了仿真,结果表明提出的算法是有效的并具有很好的灵活性。     

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.     

Joint channel and impulsive noise estimation method for OFDM systems

Aiming at the impulsive noise occurring in OFDM systems,an impulsive noise mitigation algorithm based on compressed sensing theory was proposed.The proposed algorithm firstly treated the channel impulse response and the impulsive noise as a joint sparse vector by exploiting the sparsity of both them.Then the sparse Bayesian learning framework was adopted to jointly estimate the channel impulse response,the impulsive noise and the data symbols,in which the data symbols were regarded as unknown parameters.Compared with the existing impulsive noise mitigation methods,the proposed algorithm not only utilized all subcarriers but also did not use any a priori information of the channel and impulsive noise.The simulation results show that the proposed algorithm achieves significant improvement on the channel estimation and bit error rate performance.     

OFDM-WLAN系统互相关超分辨TOA估计

在正交频分复用无线局域网系统的室内场景下,针对单快拍多重信号分类的超分辨到达时间估计由于多径数估计不准确导致的到达时间估计误差偏大的问题,提出了一种未知多径数的互相关超分辨到达时间估计算法。该算法根据正交频分复用无线局域网系统的物理层协议数据单元的特点,考虑到前导码中相邻两个长正交频分复用符号的信道不变性和噪声的不相关性,首先利用两个长正交频分复用符号估计两组信道频域响应,然后,采用前后向频域平滑的方法,求两组信道频域响应的互相关矩阵,进而用所求互相关矩阵逆的高次幂近似噪声特征矩阵的乘积,最后构造伪谱函数并进行谱峰搜索,从而实现到达时间的估计。仿真结果表明,该算法估计精度高,且对噪声不敏感,具有较好的鲁棒性。     

Totally blind APP channel estimation for mobile OFDM systems

A new two-dimensional blind channel estimation scheme for coherent detection of orthogonal frequency-division multiplexing (OFDM) signals in a mobile environment is presented. The channel estimation is based on the a posteriori probability (APP) calculation algorithm. The time-variant channel transfer function is completely recovered without phase ambiguity with no need for any pilot or reference symbols, thus maximizing the spectral efficiency of the underlying OFDM system. The phase ambiguity problem is solved by using a 4-QAM (quadrature amplitude modulation) scheme with asymmetrical arrangement. The results clearly indicate that totally blind channel estimation is possible for virtually any realistic time-variant mobile channel.     

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.     

限幅OFDM的一种信道估计优化方法

在OFDM 系统中,限幅常用于抑制信号的峰平比,而限幅会引入额外的限幅噪声,以致干扰数据和导引符号,恶化传输性能.本文针对限幅OFDM系统,提出一种基于导引符号的限幅噪声消除算法.该算法在插入导引符号之前,滤除位于导引位置的限幅噪声,从而改善信道估计性能.在此基础上,本文还提出了利用迭代算法以进一步提高信道估计精确度.本文对所提出的限幅噪声消除算法及迭代算法进行了仿真验证,结果表明,新算法能够明显改善信道估计,优化传输性能.     

Artificial Neural Network Channel Estimation Based on Levenberg-Marquardt for OFDM Systems

The many advantages responsible for the widespread application of orthogonal frequency division multiplexing (OFDM) systems are limited by the multipath fading. In OFDM systems, channel estimation is carried out by transmitting pilot symbols generally. In this paper, we propose an artificial neural network (ANN) channel estimation technique based on levenberg-marquardt training algorithm as an alternative to pilot based channel estimation technique for OFDM systems over Rayleigh fading channels. In proposed technique, there are no pilot symbols which added to OFDM. Therefore, this technique is more bandwidth efficient compared to pilot-based channel estimation techniques. Also, this technique is making full use of the learning property of neural network. By using this feature, there is no need of any matrix computation and the proposed technique is less complex than the pilot based techniques. Simulation results show that ANN based channel estimator gives better results compared to the pilot based channel estimator for OFDM systems over Rayleigh fading channel.