OFDM系统中低复杂度联合译码和信道估计方法研究

本文针对OFDM(Orthogonal Frequency Division Multiplexing)系统提出了一种低复杂度联合译码和信道估计算法的接收机。接收机首先通过导频对信道进行估计，然后使用Turbo码译码输出判决信息对信道参数进行稳健的估计。仿真结果表明，即使系统误码率大于10^-2，经过3次迭代估计，系统性能提高仍有0．5-1dB；在高信噪比下，可显著地降低系统的误码底限。本文同时还给出了译码迭代次数对系统性能的影响。     

An Adaptive Channel Estimation Technique in MIMO OFDM Systems

In this paper, an adaptive channel estimation for MIMO OFDM is proposed. A set of pilot tones first are placed in each OFDM block, then the channel frequency response of these pilot tones are adaptively estimated by reeursive least squares （RLS） directly in frequency domain not in time domain. Then after the estimation of the channel frequency response of pilot tones, to obtain the channel frequency response of data tones, a new interpolation method based on DFT different from traditional linear interpolation method according to adjacent pilot tones is proposed. Simulation results show good performance of the technique.     

一种有效的MIMO OFDM信道估计方法

传统的MIMO OFDM信道估计方法总是假设信道在由若干OFDM符号组成的每一帧的传输过程中保持不变,但这个假设在快变信道的条件下就不成立了.本文提出了一种适合快变信道的有效的估计方法.该方法通过在每个OFDM符号中设置若干训练子载波来跟踪快变的信道.首先讨论了在每个OFDM符号中所需的训练子载波的数目及其相应的位置,给出了在多发射天线多接收天线条件下的训练子载波的正交结构,然后在估计出训练子载波处的信道频率响应后.提出了一种不同于根据邻近训练子载波进行线性插值的以获得用于传输数据的子载波的信道频率响应的方法.仿真结果表明了我们所提出的方法的有效性.     

Structure-Based Low Complexity MMSE Channel Estimator for OFDM Wireless Systems

Wireless communication systems utilizing orthogonal frequency division multiplexing (OFDM) transmissions are capable of delivering high data rates over multipath frequency selective channels. This paper deals with joint estimation/interpolation of wireless channel using pilot symbols transmitted concurrently with the data. We propose a low complexity, spectrally efficient minimum mean square error channel estimator which exploits the correlation structure of channel frequency response for reducing the complexity. Specifically, it is shown that if pilots are inserted appropriately across OFDM subcarriers, the proposed algorithm requires no matrix inversion, thereby significantly relieving the computational burden without deteriorating the performance. Moreover, the knowledge of channel correlation is also not required for the proposed estimator. Simulation results validate that the proposed technique outperforms existing low-complexity variants in terms of mean square error and computational complexity.

     

Pilot-Based LMMSE Channel Estimation for OFDM Systems With Power–Delay Profile Approximation

In linear-minimum-mean-square-error (LMMSE) channel estimation for multicarrier systems, one needs to know the channel correlation function. This poses a problem for systems with a small number of pilots operating in time-varying channels. We propose to approximate the channel power–delay profile (PDP) with a shape that can completely be described in two parameters, namely, the mean delay and the root-mean-square (RMS) delay spread. Furthermore, we develop a simple technique to estimate these delay parameters. The approximate PDP is then used to generate the LMMSE filter coefficients for data-subcarrier channel estimation. Mathematical expressions are derived that can be used to predict the accuracy of the various estimates, and they are verified by simulation. The proposed technique is applicable to both point-to-point communication and multiaccess communication where different users may experience different channel conditions. As a practical application, we also specialize the proposed technique to Mobile WiMAX signals and investigate the resulting performance.      

Low Complexity Linear Channel Estimation for MIMO Communication Systems

Channel estimation is employed to get the current knowledge of channel states for an optimum detection in fading environments. In this paper, a new recursive multiple input multiple output (MIMO) channel estimation is proposed which is based on the recursive least square solution. The proposed recursive algorithm utilizes short training sequence on one hand and requires low computational complexity on the other hand. The algorithm is evaluated on a MIMO communication system through simulations. It is realized that the proposed algorithm provides fast convergence as compared to recursive least square (RLS) and robust variable forgetting factor RLS (RVFF-RLS) adaptive algorithms while utilizing lesser computational cost and provides independency on forgetting factor.     

OFDM系统信道估计算法研究

在OFDM技术应用于移动通信领域时,其信道估计技术是一项关键技术。分析了级联的一维的信道估计方法,采用加窗的方式改进了基于FFT一维级联信道估计算法,在此基础上提出一种新的基于DCT（EIDCT）变换的信道估计算法。最后给出了改进算法的性能仿真,并对仿真结果进行分析。     

基于DCT的OFDM信道估计

在宽带移动环境下,由于多普勒频移以及多径的影响,信道是时变的。为了消除信道对传输信号的影响,需要对信道进行估计。给出了2种基于离散余弦变换(DCT)的信道估计方法,可以很好的降低频谱泄露造成的混叠失真,适用于非整数倍的抽样信道。其中一种性能较好,另一种实现更加方便。仿真结果表明,这两种算法的性能均优于基于DFT的信道估计算法。     

A Novel Technique for Channel Estimation and Equalization for High Mobility OFDM Systems

Orthogonal frequency division multiplexing (OFDM) technique, when used in wireless environments, is known to be robust against frequency selective fading. However, when the channel shows time selective fading, rapid variations destroy the subcarrier orthogonality and introduce inter-carrier interference (ICI). The use of ICI mitigation schemes requires the availability of channel state information (CSI) at the receiver, which is a non-trivial task in fast fading systems. In our work, we have addressed the problem of estimation of rapidly varying channels for OFDM systems. The channel is modeled using complex exponentials as basis functions and the estimation process makes use of the cyclic prefix (CP) part available in OFDM symbols as training. The system is viewed as a state space model and Kalman filter is employed to estimate the channel. Following this, a time domain ICI mitigation filter that maximizes the received SINR (signal to interference plus noise ratio) is employed for equalization. This method performs considerably well in terms of MSE as well as BER at very high Doppler spreads.

基于导频的光OFDM系统信道估计

为了克服光纤色散和模式的传输时延导致ICI设计了一种基于导频的信道估计器．并分析了LS和LMMSE算法估计原理,通过仿真实验比较了两种算法的误比特率和均方误差性能．实验结果表明LS与LMMSE在光OFDM系统中都有较好的作用但LMMSE算法性能要优于LS算法。     

OFDM系统在动态环境下的自适应信道估计

分析了OFDM通信系统信道估计采用二维自适应维纳滤波的情形，信道估计根据对不同的信道环境（多径时延，多普勒频移）的实时检测，自适应地选择适宜的滤波参数，动态地跟踪信道的变化特征。仿真分析得到了最优的滤波参数并且证明了在非完全匹配条件下的插值亦有很好的效果。     

基于导频的光OFDM系统信道估计

信道估计是光正交频分复用（OOFDM）系统关键技术之一,为了克服光纤色散和模式的传输时延所产生的载波间干扰（ICI）,设计了一种基于导频的信道估计器,通过分析最小二乘（LS）和线性最小均方误差（LMMSE）算法估计原理,仿真实验比较两种算法的误比特率和均方误差性能,实验结果表明,LS与LMMSE在OOFDM系统中都有较好的作用,但LMMSE算法性能要优于LS算法。     

Joint Synchronization and Channel Estimation for OFDM Systems

1Introduction Orthogonal Frequency Division Multiplexing(OFDM) has become a popular technique for transmis-sion of signals over wireless channels . OFDMhas beenadoptedinseveral wireless standards such as Digital Au-dio Broadcasting ( DAB) , Digital Video Broadcasting(DVB-T) ,the IEEE 802 .11a[1]Local Area Network(LAN) standard and high performance LAN type 2(HIPERLAN/2)[2]standard. OFDMis also being pur-sued for Dedicated Short-Range Communications(DSRC) for road side to …     

Fast Synchronization and Channel Estimation for OFDM Systems

A joint synchronization and channel estimation scheme is proposed for orthogonal frequency division multiplexing (OFDM) system. In the proposed scheme, the integer frequency offset, fine timing offset and channel estimation are estimated based on the characteristics of the chirp signals. The main contributions of the paper are: the more robust ability to find the actual first path instead of the strongest path on the assumption of repeated chirp waveforms in the timing synchronization approach, and the lower computational complexity with high performance in the channel estimation approach. Moreover, we analyze the performance of the proposed method and check it via Monte Carlo simulations. The simulation results show that the proposed method can achieve good performance for both synchronization and channel estimation in frequency selective channels.     

OFDM系统中的盲信道估计

本文从OFDM信号的矩阵表示出发,分析比较了OFDM系统中现有的各种盲信道估计方法。OFDM盲信道估计方法分为两类,一类是统计型方法,它利用了发送信号和接收信号的统计特性;另一类是确定型方法,它利用了发送调制信号的固有特性。一般而言,统计型方法的计算量较小,但是估计精度不高且估计的实时性不好;而确定型方法的估计精度较高,实时性较好,但是其计算量较大。计算机仿真表明,这些盲信道估计方法的性能受信道参数尤其是多普勒频率影响很大,盲信道估计的实用化有待进一步研究。     

Sparse Approximations of the LMMSE Channel Estimation in OFDM with Transmitter Diversity

The linear minimum mean-squared error (LMMSE) channel estimation for orthogonal frequency-division multiplexing (OFDM) systems requires a large number of complex multiplications. We evaluate a simplified LMMSE channel estimation algorithm in a transmit diversity environment by applying a significant weight catching (SWC) technique to the LMMSE fixed weighting matrix. The SWC technique itself is based on modifying the smoothing matrix by leaving the Γ largest values in each row and turning the rest to zeros. This allows the computational complexity of the full LMMSE processor to be reduced by more than 50%. In the well known LMMSE by singular value decomposition (SVD) technique the sparse approximation is accomplished by zeroing out all but the r largest singular values. LMMSE by SVD is the preferred approximation technique for low delay spread channels. However, in channels with large delay spreads, LMMSE by SWC is a better choice in terms of computational complexity and estimation accuracy Igor Tolochkoreceived his Dipl.-Eng. Degree in Electrical Engineering from Polytechnic Institute, Riga, Latvia in 1987 and PhD from Victoria University, Melbourne, Australia in 2005. He was a senior and later principal design engineer in mobile communications at the Riga Semiconductor Institute Alpha (1988 – 1993). During 1993 – 1998, he was involved in research and development activities in communications with different companies in Riga and Melbourne, Australia. From 1998 to 2002, he was with Ericsson Australia as a senior design engineer. Currently, he works for NEC Australia Pty. Ltd. as a senior design engineer in 3G Mobile Department. His current research interests include digital signal processing, indoor and outdoor wireless communications and error control coding. Michael Faulkner(M'84) received the B.Sc. (Eng) from Queen Mary College, London University, UK, in 1970, the M.E. degree from the University of New South Wales, Australia in 1978, and the PhD from University of Technology Sydney in 1993. From 1972 to 1975 he was with STC (now Alcatel) Australia. From 1975 to 1977 he as with the University of New South Wales, and since then as a lecturer and now professor at Victoria University of Technology, Melbourne, Australia where he is director of the Telecommunications and Micro-electronics research centre. Between 1988 and 2000 he spent four periods at Lund University, Sweden. He was co-recipient of the IEE's 1997 IERE prize for a paper on amplifier linearisation. His current interests are, signal processing, radio technology, radio systems and MIMO/OFDM.     

基于DFT的OFDM系统信道估计改进算法

基于DFT的信道估计算法计算复杂度比MMSE算法低,性能比LS算法好.但是传统的基于DFT的信道估计只消除了信道冲击响应估计中循环前缀长度之外的噪声,循环前缀长度内的噪声并没有得到抑制,因此算法性能还有提高的空间.本文提出了一种改进的基于DFT的信道估计算法.算法首先估计出噪声方差,然后利用噪声方差设定一个门限,通过此门限对循环前缀内的信道时域冲击响应值进行阈值,进一步消除噪声的干扰.仿真证明,本文的改进信道估计算法性能优于原算法.     

Adaptive Channel Estimation for Multiple Antenna OFDM Systems

We propose a simple adaptive algorithm for channel estimation of multiple antenna OFDM systems to provide competitive performance with low computational complexity and tracking ability. The derivation of the mean-squared error (MSE) for the proposed scheme is presented and the optimum selection of the parameter in the scheme is analyzed by utilizing the derived MSE expression.     

Wavelet-Based Semiblind Channel Estimation for Ultrawideband OFDM Systems

Ultrawideband (UWB) communications involve very sparse channels, because the bandwidth increase results in a better time resolution. This property is used in this paper to propose an efficient algorithm that jointly estimates the channel and the transmitted symbols. More precisely, this paper introduces an expectation-maximization (EM) algorithm within a wavelet-domain Bayesian framework for semiblind channel estimation of multiband orthogonal frequency division multiplexing based UWB communications. A prior distribution is chosen for the wavelet coefficients of the unknown channel impulse response to model a sparseness property of the wavelet representation. This prior yields, in maximum a posteriori estimation, a thresholding rule within the EM algorithm. We particularly focus on reducing the number of estimated parameters by iteratively discarding “insignificant” wavelet coefficients from the estimation process. Simulation results using UWB channels that were issued from both models and measurements show that, under sparseness conditions, the proposed algorithm outperforms pilot-based channel estimation in terms of the mean square error (MSE) and bit error rate (BER). Moreover, the estimation accuracy is improved, whereas the computational complexity is reduced compared with traditional semiblind methods.      

OFDM系统中的信道估计方法分析

对信道估计有利于消除信道对OFDM系统性能的影响。本文探讨了OFDM系统中信道估计的多种方法,重点对MMSE(最小均方误差)、LS(最小平方)、PSAM(导频辅助调制)和盲的信道估计方法及它们的特点进行了分析和比较。