Robust and Improved Channel Estimation Algorithm for MIMO-OFDM Systems

Multiple-input multiple-output (MIMO) system using orthogonal frequency division multiplexing (OFDM) technique has become a promising method for reliable high data-rate wireless transmission system in which the channel is dispersive in both time and frequency domains. Due to multiple cochannel interferences in a MIMO system, the accuracy of channel estimation is a vital factor for proper receiver design in order to realize the full potential performance of the MIMO-OFDM system. A robust and improved channel estimation algorithm is proposed in this paper for MIMO-OFDM systems based on the least squares (LS) algorithm. The proposed algorithm, called improved LS (ILS), employs the noise correlation in order to reduce the variance of the LS estimation error by estimating and suppressing the noise in signal subspace. The performance of the ILS channel estimation algorithm is robust to the number of antennas in transmit and receive sides. The new algorithm attains a significant improvement in performance in comparison with that of the regular LS estimator. Also, with respect to mean square error criterion and without using channel statistics, the ILS algorithm achieves a performance very close to that of the minimum mean square error (MMSE) estimator in terms of the parameters used in practical MIMO-OFDM systems. A modification of the ILS algorithm, called modified ILS (MILS), is proposed based on using the second order statistical parameters of channel. Analytically, it is shown that the MILS estimator achieves the exact performance of the MMSE estimator. Due to no specific data sequences being required to perform the estimation, in addition to the training mode, the proposed channel estimation algorithms can also be extended and used in the tracking mode with decision-aided method.     

Least Square Channel Estimation for Two‐Way Relay MIMO OFDM Systems

This letter considers the channel estimation for two‐way relay MIMO OFDM systems. A least square (LS) channel estimation algorithm under block‐based training is proposed. The mean square error (MSE) of the LS channel estimate is computed, and the optimal training sequences with respect to this MSE are derived. Some numerical examples are presented to evaluate the performance of the proposed channel estimation method.     

基于信号子空间的改进OFDM系统信道半盲估计

本文改进了一种基于信号子空间的OFDM系统半盲信道估计算法.该算法利用基于梯度变化的变遗忘因子递归最小二乘算法(GVFF-RLS)计算接收信号的自相关矩阵.通过同时对角化接收信号中的信息信号和噪声信号的全局协方差矩阵,推导出噪声信号子空间,无需对噪声信号的统计特性进行任何先验假定.本算法弥补了原始算法在慢衰落信道下收敛慢以及只限于加性白噪声的不足,实现了色噪声背景下高效半盲信道估计.仿真结果表明本文提出的算法具有良好的性能.     

一种基于DFT的低复杂度虚子载波OFDM信道估计算法

该文针对采用虚子载波的OFDM通信系统,提出了一种基于DFT的低复杂度信道估计算法,并与最小二乘(Least Square,LS)估计算法和线性最小均方误差(Linear Minimum Mean Square Error,LMMSE)算法进行了详细的性能和复杂度比较。所提DFT算法较好地降低了高斯白噪声的影响,相对于LS算法获得了较大的性能增益。该算法在复杂度与性能之间取得了较好的折衷,具有很好的实用价值。     

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。     

Effects of channel estimation error on array processing based QO-STBC coded OFDM systems

This letter addresses the issues on performance degradation caused by channel estimation error of quasiorthogonal space-time block (QO-STBC) coded OFDM systems employing array processing decoder. The least square (LS) channel estimator is employed to obtain the required channel state information (CSI). Taking mean square error (MSE) as a performance metric, we evaluate the performance of the LS estimator in MIMO-OFDM systems over frequency selective channels, and its impact on symbol error rate (SER) using both analysis and simulations.     

Performance Analysis of Downlink W-CDMA Systems in Weibull and Lognormal Fading Channels Using Chaotic Codes

In this paper, a subspace based blind channel estimation scheme for downlink W-CDMA systems using chaotic codes under Weibull and Lognormal fading channel conditions is proposed and compared with W-CDMA system using PN codes. The algorithm provides estimates of multiuser channels by exploiting the structural information of the data output. The subspace of the (data + noise) matrix contains sufficient information for unique determination of channels and, hence, the signature waveforms and signal constellations. The proposed channel estimation algorithm is also implemented for multiuser—orthogonal frequency division multiplexing (OFDM) system. Performance measures like bit error rate (BER) and root mean square error (RMSE) are plotted for Weibull and Lognormal fading channels. Signal constellations under Weibull and Lognormal channels are also plotted. Analytical and Simulation results for BER and RMSE are compared for W-CDMA system using PN codes and chaotic codes. Simulation results show that, chaos-based W-CDMA outperforms the PN-based W-CDMA in terms BER and RMSE. Simulation results of multiuser-OFDM system shows that performance is further improved when compared to the W-CDMA system.     

基于噪声子空间跟踪的OFDM盲信道估计

基于子空间分解的OFDM信道估计算法利用信号子空间和噪声子空间的正交性可以对信道参数进行盲估计,但是子空间分解的运算量大,使盲信道估计算法的实用化受到限制。本文在噪声子空间自适应跟踪的基础上进行OFDM盲信道估计,显著降低了运算量。仿真结果表明,在适当选择学习因子后可以实现对噪声子空间的快速跟踪,在噪声子空间跟踪的基础上得到的信道估计性能接近于子空间分解法。     

Semiblind Channel Estimation and Signal Detection for OFDM System with Receiver Diversity

In this paper, we address the problem of channel estimation and signal detection for orthogonal frequency division multiplexing (OFDM) system with multiple receive antennas. The received signal can be denoted as a trilinear model, and then a trilinear decomposition-based channel estimation and signal detection algorithm is proposed. Scalar ambiguity which is inherent in the blind algorithms can be easily resolved by insertion fewer pilots in the proposed algorithm. Compared with conventional subspace approaches, the proposed algorithm has improved estimation performance, and the signal detection performance of the proposed algorithm is very close to non-blind minimum mean square error (MMSE) receiver. Furthermore, our proposed algorithm works well in the presence/absence of virtual carriers, and it does not require knowledge of statistical characteristics. Simulation results illustrate performance of the algorithm.     

A new optimized least-square sparse channel estimation scheme for underwater acoustic communication

In underwater acoustic (UWA) communication, orthogonal frequency division multiplexing (OFDM) is a promising technology that is highly essential to get channel state information meant for channel estimation (CE). Nevertheless, higher complexity, slower convergence, and poor performance, which degrade the performance estimation, are the limitations of the traditional CE methodologies. Thus, by amalgamating the least square (LS)-CE algorithm along with polynomial interpolated black widow optimization (PI-BWO) model, an optimized least square sparse (OLSS) CE algorithm has been proposed to intend for a UWA-OFDM communication system. Formerly, by utilizing the 2's complement shift left turbo encoding (2CSL-TE) methodology, the input signal is encoded. After that, the modulated encoded signal is provided for inverse fast Fourier transform (IFFT) operations; subsequently, they are transferred over the UWA channel toward the receiver OFDM. By employing the OLSS methodology, the received OFDM signal's interference-free region is utilized for sparse CE at the receiver. Regarding symbol error rate (SER), bit error rate (BER), mean square error (MSE), and peak signal-to-noise ratio (PSNR), the proposed model's experiential outcome is evaluated and analogized with the other prevailing methodologies. When analogized with the conventional models, the proposed estimation methodologies achieved better performance.     

Improved Channel Estimation Based on Parametric Channel Approximation Modeling for OFDM Systems

Orthogonal frequency division multiplexing (OFDM) together with high order modulation scheme requires accurate channel estimation to perform coherent demodulation. In this paper, improved channel estimation methods based on a parametric channel approximation model are proposed for the OFDM system using pilot subcarriers. This channel model is called fraction taps channel approximation (FTCA) model, which is defined as a finite impulse response (FIR) on some definitive delay taps that have a fraction tap delay spacing relative to the sampling interval. Then, based on the FTCA channel model, the minimum mean square error (MMSE) and least square (LS) estimators are derived. Simulations over non-sample-spaced channels prove that the use of the FTCA channel model can effectively eliminate the problem of multi-path delay estimation and reduce the signal subspace dimension of the channel correlation matrix, where the full-rank estimators using pilot subcarriers can be adopted, and consequently, improve the channel estimation performance.     

Pilot Tones Optimization Using Artificial Bee Colony Algorithm for MIMO–OFDM Systems

How to design the pilot tones that are used in channel estimation has a significant effect on the estimation performance. To achieve good performance in least square (LS) algorithm, we propose the artificial bee colony (ABC) algorithm for optimizing the placement of pilot tones in MIMO–OFDM systems. We also derive the upper bound of mean square error of LS estimation with the help of Gerschgorin disc theorem for fitness function of ABC algorithm. The results show that designing pilot tones using the ABC algorithm outperforms other considered placement strategies in terms of high system performance and low computational complexity.     

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。     

基于SAMP重构算法的OFDM系统稀疏信道估计方法

为了提高OFDM系统稀疏信道估计的精度和减少导频子载波的数目,本文将OFDM系统频率选择衰落信道时域稀疏冲激响应的参数估计问题转化为压缩感知理论中在稀疏度未知及存在噪声干扰情形下复数稀疏信号的重构问题,提出了分别基于基追踪降噪（BPDN）和稀疏度自适应匹配追踪（SAMP）的两种OFDM系统稀疏信道估计方法。在导频数和信噪比均相同的情形,与传统的最小二乘法（LS）、匹配追踪-最小二乘法（MP-LS）的信道估计方法相比,仿真结果表明所提出的两种方法无须将信道的稀疏度作为先验知识,并具有归一化均方误差小和误比特率低的优点。在所提出的两种方法中,基于SAMP的方法比基于BPDN的方法具有运行速度快、性能更接近Cramer-Rao界的优点,且导频子载波仅为系统子载波的12.5%,信噪比约大于10dB时,采用基于SAMP的方法在信道稀疏度未知的情形也能获得满足实际应用的误比特率。      

A subspace blind channel estimation method for OFDM systems without cyclic prefix

We propose a subspace based blind channel estimation method for orthogonal frequency-division multiplexing (OFDM) systems over a time-dispersive channel. Our approach is motivated by the resemblance of the multichannel signal model resulting from oversampling (or use of multiple receive sensors) of the received OFDM signal to that in conventional single carrier system. The proposed algorithm distinguishes itself from many previously reported channel estimation methods by the elimination of the cyclic prefix, thereby leading to higher channel utilization. Comparison of the proposed method with other two reported subspace channel estimation methods is presented by computer simulations to support its effectiveness.     

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。     

Phase Noise Correction Based on TPS Symbols for the Chinese DTTB System

In orthogonal frequency division multiplexing (OFDM) system, phase noise (PHN) from oscillator can severely reduce the performance by causing: common phase error (CPE) and inter-carrier interference (ICI). The impact of PHN on received signal can be characterized by the circular convolution of the transmitted signal and the discrete Fourier transform (DFT) of PHN signal in frequency domain. Digital television/terrestrial multimedia broadcasting (DTMB), announced as the Chinese digital television terrestrial broadcasting (DTTB) standard, adopted the time-domain synchronous OFDM system (TDS-OFDM) system which has 36 continuous transmission parameter signaling (TPS) symbols in frequency domain which be used for PHN suppression. Based on a linearized parametric model for PHN, least squared (LS) estimation and fast Fourier transform (FFT) approaching method for PHN correction are proposed in this paper. The effects of the PHN on channel estimation in both TDS-OFDM system and conventional cyclic prefix OFDM (CP-OFDM) are also investigated. Simulations show that the proposed algorithm can effectively reduce the PHN and improve the symbol error rata (SER) of TDS-OFDM systems over both additive white Gaussian noise (AWGN) and broadcasting multipath channel. In practice, the FFT-approaching method can be applied to the DTMB receiver-chip design directly with low implementation cost.      

基于导频信号的OFDM通信系统信道估计与跟踪

讨论了在正交频分复用(OFDM)通信系统中,基于导频信号,采用投影逼近子空间(PAST)算法实现信道的跟踪估计,在快速变化的信道中,信道阶数自动跟踪,与传统的信道估计方法相比,信道估计精度提高,均方误差减小.通过计算机模拟仿真,验证了信道估计的跟踪性能得到了改善.     

Optimal training design for MIMO OFDM systems in mobile wireless channels

This paper describes a least squares (LS) channel estimation scheme for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems based on pilot tones. We first compute the mean square error (MSE) of the LS channel estimate. We then derive optimal pilot sequences and optimal placement of the pilot tones with respect to this MSE. It is shown that the optimal pilot sequences are equipowered, equispaced, and phase shift orthogonal. To reduce the training overhead, an LS channel estimation scheme over multiple OFDM symbols is also discussed. Moreover, to enhance channel estimation, a recursive LS (RLS) algorithm is proposed, for which we derive the optimal forgetting or tracking factor. This factor is found to be a function of both the noise variance and the channel Doppler spread. Through simulations, it is shown that the optimal pilot sequences derived in this paper outperform both the orthogonal and random pilot sequences. It is also shown that a considerable gain in signal-to-noise ratio (SNR) can be obtained by using the RLS algorithm, especially in slowly time-varying channels.     

基于冲激响应加窗法的CO-OFDM系统信道估计研究

针对相干光正交频分复用(CO-OFDM)系统中光纤的色散和信号传输过程中噪声对系统可靠性的降低,提出了信道的冲激响应加窗(IRM,impulse response processed with window)算法,在最小二乘(LS)算法的基础上,通过时域加窗将信道冲激响应长度以外的噪声滤除,保证了信道冲激响应长度在OFDM保护间隔之内。在算法复杂度提高并不大的前提下,IRW算法系统误码率(BER)比LS算法降低了近1个数量级。仿真结果表明,在256个子载波的CO-OFDM系统中,BER为10-4时,IRW算法对系统信噪比(SNR)的要求比LS算法低了近2.5dB,而只比线性最小均方误差(LMMSE)算法高0.7dB;并且,IRW算法的复乘次数仅比LS算法高8倍,而比LMMSE算法的复乘次数低32倍。