MIMO-OFDM系统中基于变分贝叶斯EM算法的联合符号检测与信道估计

基于变分贝叶斯期望最大化(VBEM, variational Bayes expectation maximization)算法和Turbo原理,提出了时变信道条件下MIMO-OFDM系统中的联合符号检测与信道估计算法.设计的软入软出空时检测器在采用列表球形译码避免穷尽搜索的同时,考虑了信道估计误差方差矩阵的影响;利用空时检测获得的发送信号后验概率分布估计,推出了新的Kalman前向后向递归信道估计器.仿真结果表明,在时变多径信道条件下,提出的算法比传统EM算法和面向判决算法更加具有顽健性.     

MIMO-OFDM系统中一种改进的Bayesian EM信道估计器

该文提出了MIMO-OFDM系统中一种改进的Bayesian EM信道估计器。利用软球形译码器的搜索列表和解码器反馈的先验信息对传统EM信道估计中的软信息近似处理进行了修正,计算了更为准确的软符号后验概率分布以及一阶、二阶统计量。基于初始估计得到的信道先验信息,设计了新的考虑软符号后验互相关的时域信道冲激响应最大后验概率(MAP)估计算法。仿真试验结果表明:该算法和传统EM信道估计算法相比具有更低的误码率和更小的估计均方误差值。     

基于导频和修正Kalman滤波的MIMO-OFDM信道估计方法

提出了一种适用于时间频率选择性衰落信道的MIMO-OFDM系统的组合信道估计方法。采用AR过程对信道进行建模,利用基于导频的低维Kalman滤波算法进行信道估计,并采用LS算法估计时变的信道衰减因子。Kalman滤波跟踪了信道的时域相关性,为了同时跟踪信道的频域相关性,采用了一种基于MMSE(minimum mean square error)的合并器对Kalman滤波算法进行修正。仿真表明,提出的这种组合算法降低了传统的Kalman滤波结构的复杂度,能够跟踪信道的时频变化,改进了基于LS准则的信道估计算法,并且与复杂的高维Kalman滤波算法的信道估计性能相当。     

OFDM系统中一种新的迭代信道估计算法

本文提出了OFDM系统中一种新的基于软信息迭代处理的信道估计算法。该算法将面向判决最小二乘估计算法和盲估计算法相结合,在估计器中构造了一种新的置信度量函数,根据解码和软映射重构的反馈信号置信度大小在两种估计算法中自适应选择,这样估计的信道频响可以有效提高软信息迭代接收性能,大大降低信道估计训练开销。仿真结果表明,本文提出的算法能有效跟踪信道时变,限制传统面向判决估计的错误传播,达到好的系统性能。     

未知噪声信息多径衰落信道的软判决度量生成

信道解码中的软判决技术需要利用信道噪声方差信息来产生软判决度量,而通常情况下,这一信息是未知和时变的。本文首先简要分析了信道噪声方差对软判决度量的影响,进而提出一种新的在多径衰落信道中估计时变噪声方差的方法,并利用该方法的估计结果为信道解码器生成软判决度量。将该算法应用于中国地面数字电视广播传输系统外接收机的仿真结果表明：与已有的信道噪声方差估计算法相比,本文算法具有收敛速度快、估计结果准确的优点,生成的软判决度量逼近于多径衰落信道的最优软判决度量。     

基于FABA-SISO的时变频率选择性衰落信道CPM信号盲均衡

该文针对时变频率选择性衰落信道下高阶连续相位调制(CPM)信号盲均衡中存在的均衡性能较差、复杂度较高以及收敛速度慢等问题,从双向自适应信道均衡的角度出发,将线性调制信号均衡中使用的前后向自适应软输入软输出(FABA-SISO)算法推广,建立一种新的基于FABA-SISO的信道盲均衡方法,并结合逐幸存处理(PSP)思想和Kalman滤波,提出一种适用于高阶CPM信号的自适应盲均衡算法。该算法通过使用FABA-SISO算法,同时利用过去、现在和将来的观察数据进行Kalman滤波信道估计,有效改善了信道估计的精度,同时使用PSP算法来降低系统的复杂度,使得算法具有较好的工程应用性。仿真结果表明所提算法具有良好的盲均衡性能以及收敛性。     

频选快衰落信道的Turbo均衡算法

针对频选快衰落信道,本文提出卡尔曼滤波信道跟踪、软输出判决反馈均衡及软输入软输出信道解码迭代处理的Turbo均衡算法以充分利用已获得的信息,实现信道估计、信道均衡与信道解码的迭代更新,并克服传统判决反馈均衡器误差传播的缺陷.仿真表明,本算法能有效地跟踪快衰落信道,经两次迭代就可获得较为满意的码间干扰消除效果.     

宽带CDMA中一种新的自适应信道估计方法

在衰落信道中进行相干解调必须知道瞬时的信道参数，但由于信道是时变的，所以信道估计器的频率响应和带宽应该是由衰落信道的统计特性和系统的信干比决定。利用瞬时信道估计的自相关函数，本文提出了信道估计的一种新的自适应算法。在平坦瑞利信道中的计算机仿真表明本方法在3G标准支持的所有多普勒频率范围内都能获得良好的均方误差性能。     

MIMO-OFDM系统中基于迭代MAP算法的RLS信道估计

该文提出了一种适用于MIMO-OFDM系统的迭代最大后验概率(Iterative-MAP)信道估计算法。接收机利用MAP译码算法中的信息位和校验位软信息,经过非线性映射将信息反馈至信道估计模块,采用递归最小二乘(RLS)自适应滤波算法对信道时变状态参数进行跟踪,提高了信道估计的精度。仿真结果表明,该方法与最小二乘(LS)算法相比,估计的均方误差(MSE)和误帧率(FER)性能都有较大改善。     

一种频选衰落信道下的Turbo多用户检测算法

联合MAP多用户检测与信道解码的迭代多用户检测(MUD)技术可显著提高宽带移动CDMA系统的容量和性能.在多径时变衰落的编码信道下,提出一种迭代实现干扰抑制、符号估计、信道解码的Turbo多用户检测算法.在每次迭代中,MUD自适应地实现干扰抑制并输出符号估计的软信息,软输入软输出的信道解码器使用LOG MAP方法实现信道解码并反馈符号估计的软信息作为下一次TurboMUD迭代的先验信息.仿真结果证实了该算法在频选衰落信道下经两次迭代就能逼近单用户编码CDMA系统的接收性能.     

Adaptive Bayesian and EM-based detectors for frequency-selective fading channels

The problems of adaptive maximum a posteriori (MAP) symbol detection for uncoded transmission and of adaptive soft-input soft-output (SISO) demodulation for coded transmission of data symbols over time-varying frequency-selective channels are explored within the framework of the expectation-maximization (EM) algorithm. In particular, several recursive forms of the classical Baum-Welch (BW) algorithm and its Bayesian counterpart (often referred to a Bayesian EM algorithm) are derived in an unified way. In contrast to earlier developments of the BW and BEM algorithms, these formulations lead to computationally attractive algorithms which avoid matrix inversions while using sequential processing over the time and trellis branch indices. Moreover, it is shown how these recursive versions of the BW and BEM algorithms can be integrated with the well-known forward-backward processing SISO algorithms resulting in adaptive SISOs with embedded soft decision directed (SDD) channel estimators. An application of the proposed algorithms to iterative "turbo-processing" receivers illustrates how these SDD channel estimators can efficiently exploit the extrinsic information obtained as feedback from the SISO decoder in order to enhance their estimation accuracy.     

New List Sphere Decoding (LSD) and Iterative Synchronization Algorithms for MIMO-OFDM Detection With LDPC FEC

New sphere decoding and synchronization algorithms for multiple-input–multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems are proposed in this paper. In particular, an iterative list branch-and-bound (BB) algorithm based on the basic BB algorithm is described to obtain a candidate list to compute soft information that is used in the iterative detector. Furthermore, an improved algorithm that uses prior information from the preceding iteration to calculate the lower bound is proposed, and the candidate list is updated every iteration. To obtain a complete modem architecture, we propose an efficient expectation–maximization (EM)-based iterative algorithm for synchronization and channel estimation to interface with the proposed list-sphere-decoding detector, and we investigate the performance of the designed MIMO-OFDM modem on a realistic fading channel. The obtained performance results show that it is possible to practically design a performing MIMO-OFDM modem with high spectral efficiency, i.e., 8 bit/s/Hz with a 4 $times$ 4 16-QAM MIMO-OFDM system.      

EM-based recursive estimation of channel parameters

Recursive (online) expectation-maximization (EM) algorithm along with stochastic approximation is employed in this paper to estimate unknown time-invariant/variant parameters. The impulse response of a linear system (channel) is modeled as an unknown deterministic vector/process and as a Gaussian vector/process with unknown stochastic characteristics. Using these models which are embedded in white or colored Gaussian noise, different types of recursive least squares (RLS), Kalman filtering and smoothing and combined RLS and Kalman-type algorithms are derived directly from the recursive EM algorithm. The estimation of unknown parameters also generates new recursive algorithms for situations, such as additive colored noise modeled by an autoregressive process. The recursive EM algorithm is shown as a powerful tool which unifies the derivations of many adaptive estimation methods     

一种OFDM导频的信道估计算法的研究

提出了一种基于编码的OFDM系统的导频符号迭代辅助信道估计。利用信道解码器中的APP符号来形成虚拟的导频。与原有的信道估计算法相比,此种算法不仅在一般的信道条件下具有良好的性能,而且更加适合快变信道条件下的OFDM系统。仿真结果表明:提出的OFDM信道估计算法不仅可以给出精度较高的信道信息,而且近似达到EM信道估计的性能。     

Numeric Variable Forgetting Factor RLS Algorithm for Second-Order Volterra Filtering

Nonlinear adaptive filtering techniques for system identification (based on the Volterra model) are widely used for the identification of nonlinearities in many applications. In this correspondence, the improved tracking capability of a numeric variable forgetting factor recursive least squares (NVFF-RLS) algorithm is presented for first-order and second-order time-varying Volterra systems under a nonstationary environment. The nonlinear system tracking problem is converted into a state estimation problem of the time-variant system. The time-varying Volterra kernels are governed by the first-order Gauss–Markov stochastic difference equation, upon which the state-space representation of this system is built. In comparison to the conventional fixed forgetting factor recursive least squares algorithm, the NVFF-RLS algorithm provides better channel estimation as well as channel tracking performance in terms of the minimum mean square error (MMSE) for first-order and second-order Volterra systems. The NVFF-RLS algorithm is adapted to the time-varying signals by using the updating prediction error criterion, which accounts for the nonstationarity of the signal. The demonstrated simulation results manifest that the proposed method has good adaptability in the time-varying environment, and it also reduces the computational complexity.     

Recursive blind identification of non-Gaussian time-varying ARmodel and application to blind equalisation of time-varying channel

A novel method for the blind identification of a non-Gaussian time-varying autoregressive model is presented. By approximating the non-Gaussian probability density function of the model driving noise sequence with a Gaussian-mixture density, a pseudo maximum-likelihood estimation algorithm is proposed for model parameter estimation. The real model identification is then converted to a recursive least squares estimation of the model time-varying parameters and an inference of the Gaussian-mixture parameters, so that the entire identification algorithm can be recursively performed. As an important application, the proposed algorithm is applied to the problem of blind equalisation of a time-varying AR communication channel online. Simulation results show that the new blind equalisation algorithm can achieve accurate channel estimation and input symbol recovery     

基于空间递推的毫米波信道一致性仿真算法研究

根据鸟巢28 GHz信道测量数据,提出了一种基于空间递推的空间一致性信道大尺度参数(large-scale parameter, LSP)生成算法——空间递推算法(spatial recursion algorithm, SRA),并与传统的WINNER II算法进行了比较. SRA利用多维正态分布,通过特定的递推算法依次生成各个仿真点的信道LSP,以实现参数的自相关与互相关特性. 结果表明,在实现空间一致性的前提下,SRA仿真结果与测量数据高度吻合,仿真精度优于WINNER II算法,且SRA无需单独生成参数互相关特性,仿真步骤更为简单. SRA为相关算法的研究提供了一种新的思路,对毫米波时变信道仿真有重要意义.     

Estimation of channel statistics for iterative detection of OFDM signals

Maximum likelihood sequence estimation for orthogonal frequency division multiplexing (OFDM) transmissions over unknown multipath fading channels is analytically infeasible for lack of efficient methods to maximize the likelihood function. A practical solution to this problem has been recently proposed in the context of space-time block-coded OFDM by resorting to the expectation-maximization (EM) algorithm. The resulting detector operates iteratively, exploiting knowledge of the channel statistics and the operating signal-to-noise ratio (SNR). In this work, we address the problem of estimating the above quantities and propose a recursive solution based on ad hoc reasoning. Simulations indicate that the EM detector employing the estimated SNR and channel statistics has better performance than other schemes operating in a mismatched mode. Also, the performance loss with respect to a system with perfect channel knowledge is negligible at SNR values of practical interest.     

基于EM算法的改进OFDM时变信道估计

针对正交频分复用（OFDM）系统中的信道时变,基于时变信道的分段线性近似模型,提出一种改进的OFDM时变信道估计方案。该方案通过采用期望最大化（EM）迭代算法来提高符号平均信道脉冲响应的估计精度,从而提高时变信道估计的性能;此外,在迭代过程中进行带状子载波间干扰抑制,不仅进一步提高了时变信道估计的性能,而且降低了实现复杂度。理论分析和仿真结果表明,该算法以较低的复杂度代价有效提高了时变信道OFDM系统的性能。     

Coupled estimators for equalization of fast-fading mobile channels

This letter presents a new method for identification of fast-fading mobile channels (for which combinations of vehicle speed and carrier frequency give rise to significant fading). Our new algorithm estimates both the channel statistics and the time-varying channel impulse response on-line. Simulation studies demonstrate the performance of the new estimator which couples an augmented Kalman filter with a recursive least squares algorithm