一种水声通信Turbo均衡中的软迭代信道估计算法

 Turbo均衡技术是水声相干通信克服信道多径、消除码间干扰(ISI)的有效工具。Turbo均衡实际使用时需要对时变、多径信道进行良好的估计。为了提高信道估计的效果,该文基于时变横向滤波和相位旋转信道模型,提出一种水声通信Turbo均衡中的软迭代信道估计算法。该算法采用快速自优化最小均方算法得到各数据符号处的横向滤波器系数矢量并与二阶锁相环联合优化计算。通过仿真比较,该算法明显优于硬迭代信道估计算法,且相位估计性能优于其他文献中的软迭代信道估计算法。在海上试验中,水声通信距离5 km,方向近似垂直,接收阵起伏周期10 s,起伏幅度5 m左右,在此情况下进行数据采集。将该算法用于对海试数据的单通道Turbo均衡处理,实现无误码输出,验证了所提算法在软迭代信道相位估计方面的优势。     

利用CAZAC序列的OFDM频率同步方法

频率偏移估计是OFDM (Orthogonal Frequency Division Multiplexing)的关键技术。该文提出了在一个OFDM符号内利用两个重复的CAZAC (Constant Amplitude Zero Auto Correlation)序列进行频率偏移估计的新方法,估计范围可达整个OFDM带宽。用于同步的训练序列还可用于信道估计和均衡,这将提高系统的数据传输效率。此算法同步精度达到了Schmidl提出的Cramer-Rao bound,有效性在AWGN和Rayleigh多径信道下得到了验证。     

采用BICM-ID的PP-OFDM系统及后缀幅度优化

该文设计了一种用于正交频分复用(OFDM)系统的新型保护间隔信号-导频后缀(Pilot Postfix, PP),并构建了采用比特交织编码调制-迭代解码(BICM-ID)技术的PP-OFDM系统。PP由OFDM符号中的频域导频符号进行逆傅氏变换(IFFT)生成,在接收端可与OFDM符号中的导频相干合并,从而提高信道估计性能。该文给出了相应的信道估计、均衡和BICM-ID算法,并通过研究信道估值误差带来的接收信号有效信噪比变化,给出了PP幅度优化设计方法。仿真表明:选取适当的PP大小后,PP-OFDM比循环前缀/补零后缀-OFDM(CP/ZP-OFDM)的信道估计性能更好,误包率更低。     

基于深度学习的单载波频域均衡算法研究

单载波频域均衡(Single-Carrier Frequency-Domain Equalization,SC-FDE)是一种有效的抗码间干扰的算法,在无线通信系统中得到了广泛的应用.传统线性SC-FDE算法主要包括信道估计、噪声功率估计和信道均衡三个模块,其中每个模块都是单独优化的.为了联合优化这三个模块,本文提出了...     

瑞利衰落信道下的Turbo均衡

Turbo均衡是一种将Turbo原理和均衡技术结合起来的技术。他通过反复均衡和信道译码来提高接收机性能。针时瑞利衰落信道，采用基于线性滤波器的软输入／软输出均衡器来消除码间干扰，其系数由最小均方误差准则确定。译码器采用最大后验概率算法时卷积码译码。考虑到瑞利衰落信道为随机信道，用非相干检测时信道进行估计。接收机通过联合均衡和译码以充分利用已经获得的信息，实现信道估计及信道均衡与信道译码的迭代更新。仿真结果表明其性能不仅远远优于非迭代系统．而且在信噪比高于4dB时几乎可以完全消除符号间干扰的影响，与MAPSE相比其复杂度大大降低。     

数字并行接收机在时变信道下的信道估计与均衡方法

为了适应高速宽带无线通信的需要,本文在一种高速数字并行接收机(APRX)结构的基础上,提出了一种时变信道下的信道估计和均衡方法。使用伪随机(pseudo-randomnumber,PN)序列相关进行信道估计,将所得到的信道频率响应粗估计按照一个DFT块的长度在一帧内进行线性内插得到信道频率响应细估计,将其用来在频域进行信道均衡。这种结构能适应高速率传输的要求,并且能有效地对抗时间和频率选择性衰落。仿真结果表明,在多径衰落信道下,APRX已经无法工作,而本文提出的数字并行接收机的信道估计和均衡方法有较好的性能,并且该方法实现简单,便于应用。     

非线性卫星信道下的粒子滤波盲均衡方法

针对卫星信道中高功率放大器产生非线性失真的问题,本文提出了一种基于粒子滤波技术的盲均衡法。该算法优势在于不需要对非线性信道线性化处理,而是利用带权值的离散随机样本点来对期望分布进行近似,通过将非线性模型建模成状态空间模型,对信道参数进行跟踪和符号序列估计。仿真结果表明,算法实现了对放大器非线性幅度和相位特性的粒子滤波估计,并对符号序列进行了盲恢复,在误比特率为 较截断Volterra均衡有1.5 dB左右的性能增益;通过增加粒子数目和平滑长度能一定程度上提高算法性能,但在复杂度与性能折中考虑下,不能无限增加粒子数目。      

基于平行因子分析的SIMO-OFDM系统盲信道与符号联合估计算法

针对SIMO-OFDM系统下的信道估计和符号检测问题,该文建立了接收数据矩阵的平行因子分析(PARAFAC)模型,利用PARAFAC模型中离散傅里叶变换矩阵的行满秩特性,结合数据矩阵的奇异值分解,提出了一种信道与符号联合盲估计的闭式求解方法。由于提出的求解方法无须进行迭代便可以完成信道估计和符号检测,因此其计算复杂度低,此外,利用PARAFAC模型实现信道和符号的同时计算,避免了因信道估计误差导致的符号误码率性能下降问题。仿真结果表明,与传统方法相比提出的方法计算复杂度更低,估计性能更好。     

Iterative multiuser detection with integrated channel estimation for coded DS-CDMA

A practically interesting approach for iterative channel estimation, multiuser detection, and single-user decoding based on maximum a posteriori symbol-by-symbol estimation for direct sequence/code-division multiple-access (DS-CDMA) is proposed. The receiver relies on the output of a bank of matched filters for each user and each path, and combines interference cancellation with iterated soft-decision feedback to improve channel estimation accuracy and data symbol reliability in course of a few iterations. We show that in this way, near single-user channel phase and amplitude estimation accuracy is achieved for frequency-selective fading channels, even in highly loaded systems, and illustrate that reliable data symbol estimation can be performed.     

基于DDEA算法的短波信道Turbo均衡研究

针对数据引导均衡算法（DDEA）的缺陷,受到Turbo均衡中迭代思想的启发,提出一种基于数据引导均衡技术的短波迭代信道估计、均衡和译码算法,不仅均衡和译码之间互相传递软信息,信道估计器使用的也是译码器反馈的软信息,通过每次迭代时软信息质量的改善,提高系统的可靠性;通过多次迭代信道估计器输出的信道参数很接近当前帧的实际信...     

Blind identification and equalization based on second-orderstatistics: a time domain approach

A new blind channel identification and equalization method is proposed that exploits the cyclostationarity of oversampled communication signals to achieve identification and equalization of possibly nonminimum phase (multipath) channels without using training signals. Unlike most adaptive blind equalization methods for which the convergence properties are often problematic, the channel estimation algorithm proposed here is asymptotically ex-set. Moreover, since it is based on second-order statistics, the new approach may achieve equalization with fewer symbols than most techniques based only on higher-order statistics. Simulations have demonstrated promising performance of the proposed algorithm for the blind equalization of a three-ray multipath channel     

Theoretical studies and efficient algorithm of semi-blind ICI equalization for OFDM

The intercarrier interference (ICI) due to the Doppler frequency shift, sampling clock offset, time-varying multipath fading and local oscillator frequency offset becomes the major difficulty for the data transmission via the wireless orthogonal frequency division multiplexing (OFDM) systems. The existing ICI mitigation schemes involve the frequency-domain channel estimation/equalization or the additional coding and therefore require the pilot symbols which reduce the throughput. The frequency-domain channel estimation/equalization relies on the huge matrix inversion with high computational complexity especially for the OFDM technologies possessing many subcarriers such as digital video broadcasting (DVB) systems and wireless metropolitan-area networks (WMAN). In our previous work, we proposed a semi-blind ICI equalization scheme using the joint multiple matrix diagonalization (JMMD) algorithm and empirically showed that the proposed method significantly improved the symbol error rates for QPSK- and 16QAM-OFDM systems. In this paper, we discuss the sufficient condition for the theoretical ICI equalizability and also propose an alternative semi-blind ICI equalization method based on the joint approximate diagonalization of eigen-matrices (JADE) algorithm, which is much more computationally efficient than our previous method.     

Shifted Known Symbol Padding for Efficient Data Communication in a WLAN Context

To allow for a computationally efficient equalization scheme for the frequency-selective transmission channels encountered in wireless local area network (WLAN) applications, cyclic prefix (CP) block transmission schemes have been proposed, such as single-carrier CP (SC-CP) and multi-carrier CP (MC-CP) transmission, also known as orthogonal frequency division multiplexing (OFDM). In this letter, however, we focus on the known symbol padding (KSP) transmission scheme. In this scheme known padded sequences can be exploited for synchronization as well as for channel estimation. However, to simultaneously allow for low-complexity frequency-domain equalization and accurate channel estimation within the KSP context, a modified KSP scheme is proposed, namely shifted KSP (S-KSP). Comparing different block transmission schemes in the WLAN context, the S-KSP scheme is shown to offer a very good performance.     

基于EM-SBL迭代的稀疏SIMO信道频域盲均衡算法

针对单输入多输出系统下稀疏信道均衡问题,提出了一种新的基于最大似然准则的频域迭代均衡算法.首先将多天线联合均衡问题建模为非完整观测数据集下频域信号序列的最大似然估计问题,利用期望最大化算法进行近似迭代求解,最终得到各个单频信号加权求和形式的均衡输出表达式.在每次迭代过程中,算法依次完成均衡输出的更新和信道参数联合条件后验分布的更新.考虑到信道固有的稀疏特性,在求解信道参数联合条件后验时,引入具有稀疏促进作用的先验分布对信道系数加以约束,使用稀疏贝叶斯学习迭代求解信道参数联合条件后验.仿真结果表明,本文算法具有较好的收敛特性和稳态性能,在中高信噪比条件下可以获得接近信道已知条件下的稳态系统误符号率性能.     

Robust blind channel estimation algorithm for linear STBC systems using fourth order cumulant matrices

A novel blind channel estimation algorithm, based on fourth-order cumulant matrices, is proposed and applied to linear Space–Time Block Coded (STBC) for Multiple Input Multiple Output systems. Contrary to subspace and Second-Order Statistics (SOS) methods, the presented approach estimates the channel matrix without any modification of the transmitter. It takes advantage of the statistical independence of the signals in front of the space–time encoding. In this paper, the presented algorithm estimates the channel matrix by minimizing a cost function based on the higher cumulant matrices after Zero-Forcing equalization to mitigate the computational complexity and improve the performance. We employ the proposed method to the STBC systems including Spatial Multiplexing, Orthogonal, quasi-Orthogonal and Non-Orthogonal STBC systems. Symbol error rate and Normalized Mean Square Error simulations of the proposed algorithm are shown for a different number of users, signal to noise ratios and different number of symbols per user in comparison with subspace and Second-Order Statistics (SOS) methods. The results show that the presented method performs well and outperforms other methods in estimating the channel matrix from the received data. Moreover, the proposed method presents high convergence speed in estimating the channel matrix.     

Reduced-complexity equalization techniques for broadband wirelesschannels

This paper presents reduced-complexity equalization techniques for broadband wireless communications, both outdoors (fixed or mobile wireless asynchronous transfer mode (ATM) networks) and indoors [high-speed local-area networks (LANs)]. The two basic equalization techniques investigated are decision-feedback equalization (FE) and delayed decision-feedback sequence estimation (DDFSE). We consider the use of these techniques in highly dispersive channels, where the impulse response can last up to 100 symbol periods. The challenge is in minimizing the complexity as well as providing fast equalizer start-up for transmissions of short packets. We propose two techniques which, taken together, provide an answer to this challenge. One is an open-loop timing recovery approach (for both DFE and DDFSE) which can be executed prior to equalization; the other is a modified DFE structure for precanceling postcursors without requiring training of the feedback filter. Simulation results are presented to demonstrate the feasibility of the proposed techniques for both indoor and outdoor multipath channel models. The proposed open-loop timing recovery technique plays a crucial role in maximizing the performance of DFE and DDFSE with short feedforward spans (the feedforward section of DDFSE is a Viterbi sequence estimator). A feedforward span of only five is quite sufficient for channels with symbol rate-delay spread products approaching 100. The modified DFE structure speeds up the training process for these channels by 10-20 times, compared to the conventional structure without postcursor precancellation. The proposed techniques offer the possibility of practical equalization for broadband wireless systems     

Channel estimation and equalization for M-QAM transmission with ahidden pilot sequence

Blind equalization techniques are useful to counteract multipath effects in radio local loop (RLL) and in general for wireless point to multipoint transmissions. One of the main drawbacks of blind equalization is the slow convergence time of the equalizer. Another major problem of blind equalization is the possible convergence toward wrong solutions. When these two main disadvantages cannot be tolerated it is necessary to adopt trained channel estimation and/or equalization techniques to counteract multipath. The training sequence is usually time division multiplexed with the informative sequence. This solution reduces the bandwidth efficiency and can be unusable when too frequent updating of the communications parameters need to be performed in the receiver. It is shown that bandwidth efficiency can be preserved at the expense of an increase in the transmitted power. The additional transmitted power is used to send a known pilot sequence hidden into the informative sequence. The hidden sequence is superimposed onto the symbols to be transmitted before waveform modulation. Thus each pilot symbol has the same period of the informative symbol so that no bandwidth spreading is necessary. High spectral efficiency M-QAM modulation is considered but the technique can be easily extended to any type of digital modulation format. We analyze the problems of channel estimation and of equalization based on the hidden pilot sequence. To prove the effectiveness of the proposed technique simulation results are provided. It is observed that in the case of equalization a pilot recovery subsystem should be used before using the pilot to train the equalizer     

A time-domain estimation method of rapidly time-varying channels for OFDM-based LTE-R systems

This paper addresses the performance of fast doubly selective fading channel estimation combined with Inter-Carrier Interference (ICI) cancellation for Long Term Evolution (LTE) communication platform in the High Speed Railway (HSR) environment. We consider the Channel Impulse Response (CIR) coefficients with a critical Doppler frequency shift and multi-path fading that were taken from the WINNER II channel model and the D2a propagation scenario, where the conditions of HSR are analyzed. As multi-path fading increases and the channel varies in the order of the symbol period, we first propose a novel approach for designing a pilot symbol structure in the time domain. Then, we describe the deployment of the proposed pilot symbol structure to estimate the channel in the time domain. Channel information corresponding to the data positions is obtained by linear interpolation. In each OFDM symbol, the slope and the initial value for establishing an interpolation function are estimated to adapt to the time variation of the channel. An accurate estimate of channel state information is used for the purpose of ICI cancellation. The simulation results show that the channel estimated by our proposed method can follow the real channel well, even in a very high Doppler frequency. The estimation method in terms of Mean Squared Error (MSE) significantly outperforms the state-of-the-art methods. The combination of our channel estimator with several interference cancelers provides a considerably better system performance than that achieved when frequency channel estimation is used.     

Semi-blind identification of ARMA systems using a dynamic-based approach

A novel dynamic-based semi-blind approach is proposed to identify an autoregressive and moving average (ARMA) system in this paper. By using a chaotic driving signal, an ARMA system can be identified accurately by a dynamic-based estimation method called the ergodic-based minimum phase space volume (EMPSV). A maximum-likelihood formulation of EMPSV is provided to certify its unbiasedness and asymptotical efficiency. Monte Carlo simulations show that the EMPSV approach has a smaller mean-square error performance than the minimum phase space volume method and the conventional identification approach based on least-squares estimation with white Gaussian probing signals. The proposed approach is then applied to blind deconvolution of real audio signals and semi-blind channel equalization for chaos communications. It is shown that the EMPSV approach has improved deconvolution and equalization performances compared to conventional techniques in both applications.     

一种新的半盲联合信道数据估计算法

提出一种新的半盲联合信道估计与数据检测器,通过将递归-EM信道估计算法嵌入Turbo均衡器中,根据接收信号进行逐符号信道估计,不但能够适应时变信道,而且有效提高了联合信道数据估计收敛速度。仿真表明本算法对初始信道响应估计精度要求很低,从而大大降低了对训练序列长度的要求,使用很短的训练序列就能够达到较好性能,有效提高了频谱利用率。