Understanding the Time and Frequency Varying Characteristics of a Multipath Wireless Channel

Designing a spectrally efficient wireless channel requires a comprehensive understanding of its time and frequency varying characteristics, making it a stochastic medium of communication. These characteristics become more challenging to cater at the receiving terminal in a multipath transmission. This is because of the fading effect and Doppler shift of the transmitted frequency, specifically in cellular mobile radio systems and vehicle to vehicle communications. This paper presents the modeling, simulation, and then characterization of a cellular mobile radio multipath channel over its time and frequency varying fading gain. For this purpose, a discrete-time Finite Impulse Response (FIR) type filter of such a channel is designed, modeled, and simulated using time and frequency varying characteristics of the received signal. The simulated channel response is further analyzed in terms of coherence bandwidth, coherence time, delay spread, Doppler spread, and symbol time.

     

快速时变信道中几种自适应信道估计算法的比较研究

主要研究了MIMO-OFDM系统中快速时变信道的信道估计问题,将3种自适应信道估计算法: RLS,QRD-RLS,IQRD-RLS,应用于快速时变信道进行比较研究,并对其进行计算机仿真。仿真结果表明,3种算法性能相似,其中,QRD-RLS和IQRD-RLS算法的收敛速度要快于RLS算法,对于实时系统而言,这两种算法的效率更高。因此,QRD-RLS和IQRD-RIS算法更适合于快速时变信道。     

Time‐Varying Multipath Channel Estimation with Superimposed Training in CP‐OFDM Systems

Based on superimposed training methods, a novel time‐varying multipath channel estimation scheme is proposed for orthogonal frequency division multiplexing systems. We first develop a linear least square channel estimator, and meanwhile find the optimal superimposed sequences with respect to the channel estimates’ mean square error. Next, a low‐rank approximated channel estimator is obtained by using the singular value decomposition. As demonstrated in simulations, the proposed scheme achieves not only better performance but also higher bandwidth efficiency than the conventional pilot‐aided approach.     

多径环境下距离与深度估计性能研究

多径时延可用于估计水下声源距离与深度,由时延估计协方差矩阵可知这些时延存在一定的相关性,时延的相关性影响距离深度估计方差,仅利用独立时延可提高估计精度。分析了存在直达波与水面反射两路多径情况下时延估计相关性及其对距离与深度估计的影响,并给出了仿真结果。     

Fundamental Limit of OFDM Range Estimation in a Separable Multipath Environment

In this paper, orthogonal frequency division multiplexing (OFDM) for time-based range estimation (TBRE) in a separable multipath channel is investigated and analyzed with respect to its accuracy. First, the Cramer–Rao lower bound (CRLB) in a separable multipath channel is theoretically derived, and indicates a similar expression to that for a single path channel. The CRLB for non-data-bearing (NDB) OFDM transmission is compared to that for pseudo-noise (PN) transmission, demonstrating a large performance gap in favor of the NDB OFDM. Furthermore, the maximum likelihood estimator (MLE) for TBRE in a separable multipath channel is theoretically derived, also demonstrating a similar expression to that in a single path channel, except that several peaks instead of one peak are expected in a separable multipath channel corresponding to all arrival paths. The MLE for TBRE is then compared to the commonly used MLE for channel estimation, showing an equal performance in terms of mean square error when using an NDB OFDM transmission. Simulation results demonstrate a good agreement with our proposed theory.     

一种基于基扩展模型的OFDM频域快时变信道估计方法

现有的OFDM系统快时变信道估计方法均为时域估计方法,假定信道为整数倍采样信道,利用理想的等间隔均匀导频恢复信道时域响应函数,进而采用基扩展模型拟合并估计其时变特性。而实际的信道通常为非整数倍采样信道,频带内可用的导频也并非假定的理想模式。此时,恢复的信道时域响应出现能量泄漏,导致算法性能大大受限。本文提出一种频域快时变信道估计方法,利用信道频域时变传输函数辅助估计,从而估计得到信道频域响应矩阵。该方法在频域实现,性能不受信道时域响应能量泄露影响。仿真实验从误码率、均方误差两方面分别验证了该方法的有效性。     

Improved Soft Iterative Channel Estimation for Turbo Equalization of Time Varying Frequency Selective Channels

In this paper, we present computationally efficient iterative channel estimation algorithms for Turbo equalizer-based communication receiver. Least Mean Square (LMS) and Recursive least Square (RLS) algorithms have been widely used for updating of various filters used in communication systems. However, LMS algorithm, though very simple, suffers from a relatively slow and data dependent convergence behaviour; while RLS algorithm, with its fast convergence rate, finds little application in practical systems due to its computational complexity. Variants of LMS algorithm, Variable Step Size Normalized LMS (VSSNLMS) and Multiple Variable Step Size Normalized LMS algorithms, are employed through simulation for updating of channel estimates for turbo equalization in this paper. Results based on the combination of turbo equalizer with convolutional code as well as with turbo codes alongside with iterative channel estimation algorithms are presented. The simulation results for different normalized fade rates show how the proposed channel estimation based-algorithms outperformed the LMS algorithm and performed closely to the well known Recursive least square (RLS)-based channel estimation algorithm.     

基于改进SAMP算法的UWB多径信道估计

稀疏度自适应匹配追踪（SAMP）算法重构过程中存在其迭代终止条件设置不够合理的情况,需要对SAMP算法进行改进.在信道稀疏度未知时,改进SAMP算法依据残差之差的相对能量小于设定的停止门限来终止迭代过程,通过自适应调整可变步长逐步逼近信道的稀疏度,从而实现了重构UWB信道.仿真结果表明,改进SAMP算法低信噪比时重构精度高于SAMP算法,具有更好的重构性能和广泛的实用性.     

基于循环平稳性的约束自适应多径时延估计

在有多径信号、多通道非平稳干扰信号以及平稳背景噪声的情况下,不考虑多径信号传输的时延估计方法不能准确地估计时延,甚至估计性能会恶化.为此,本文提出了基于循环平稳性的约束自适应多径时延估计算法,并对算法的收敛性能进行了分析.该算法可以有效地抑制干扰和噪声的影响,在低信噪比的情况下直接地、准确地进行自适应多径时延估计,特别对噪声是空间相关的情形也适用,克服了传统算法不能直接估计非整数倍采样间隔的时延和多径时延的缺点.计算机仿真试验验证了新方法的有效性.     

小尺度时变多径衰落信道的仿真研究

从理论上分析了多径效应和多普勒效应对无线信道的影响,并分别从时域和频域给出了信号经历信道后的仿真图形,分析了典型时变多径衰落信道理论模型,并在此基础上建立了抽头延迟线（TDL）的确定性仿真模型;仿真分析表明,通过改变时延功率谱和确定性模型的参数计算方法,此模型可以进一步扩展并用于多种传播环境下的小尺度衰落仿真。     

Robust Channel Estimation Under Impulsive Noise for Multipath Fading CDMA Systems

This paper proposes a novel fuzzy channel estimator for direct-sequence code-division multiple-access systems with time-varying multipath fading channels under impulsive noise. The proposed estimator combines a least-squares channel estimator with a fuzzy median filter which is based on fuzzy rank ordering of samples. Simulation results clearly show the superior channel estimation success of the proposed estimator under highly impulsive noise.     

一种多径环境下麦克风阵列时延估计算法

针对多径环境下麦克风阵列时延估计问题,将归一化最小均方误差法(NLMS)与互关联法(CR)相结合,提出了NLMS-CR算法.对该算法的结构和原理进行了详细的分析,并将其与传统的相位变换广义互相关法(GCC-PHAT)和NLMS进行了比较;同时,在不同的信噪比(SNR)与声源环境下验证了该算法的效能.仿真结果表明:在较严重的多径环境下,NLMS-CR的性能优于其他传统的算法;当信噪比较高且接收信号相关性较低时,NLMS-CR具有很高的时延估计准确率.     

一种鲁棒的变导频功率多径信道估计方法

文章提出了一种基于一阶统计量变导频功率多径信道估计方法,导出了信道估计和方差运算表达式,进行了估计器性能及峰均功率比分析.没有信息速率损失,且具有很强的估计鲁棒性.理论分析和仿真结果均证明了该方法的有效性.     

Improved ML Channel Estimation for Uplink MC-CDMA Systems in Closely Spaced Multipath Channels

In order to attain near-single user performance in uplink multicarrier code- division multiple-access (MC-CDMA) systems, multiuser detection (MUD) methods may be employed which rely on simultaneous estimation of the channel frequency responses of multiple users. Pilot symbol assisted (PSA) channel estimation is needed in fast fading channels and it can be performed either by applying maximum likelihood (ML) criterion or minimum mean-squared error (MMSE) criterion. The performance of ML estimation technique degrades significantly in the case of fractionally spaced (FS) multipath channels where dominant paths are closely spaced with respect to the time resolution of the system. In such situation, the number of effective paths (which contribute more towards signal power) becomes considerably less than the actual number of multipaths at low and moderate SNR values. We propose an improved ML estimation method which considers only effective paths during the estimation process. The proposed method performs nearly identical to the MMSE estimation method and it can also provide significant reduction in the computational complexity when a large number of users are accommodated in the system.     

An Improved DFT-Based Channel Estimation Algorithm for OFDM System in Non-sample-Spaced Multipath Channels

It is well known that channel impairment caused by multipath reflections can deeply degrade the transmission efficiency in wireless communication systems. The conventional DFT-based channel estimation methods improve the performance by neglecting nonsignificant channel taps. However, in multipath channels with non-sample-spaced time delays, this will cause power leakage and result in an error floor. In order to overcome this problem, based on the property of Channel impulse response, we describe a utility of channel estimation technology for OFDM systems using discriminant analysis. Usually, significant channel taps are detected on the basis of a predetermined threshold, so the optimal threshold value becomes a crucial factor. But it is difficult to decide channel taps that are approximately equal to the threshold value. To solve this disadvantage, the proposed algorithm improves performance by using Mahalanobis distance discriminant analysis for channel taps. This approach can mitigate the aliasing effect in the DFT-based channel estimator and reduce the leakage power efficiently when there is non-sample-spaced path delay. Simulation results show that the proposed channel estimators can eliminate the error floor substantially and its performance is better than the LS and conventional DFT estimators.     

Comparative Analysis of ML-PSO DOA Estimation with Conventional Techniques in Varied Multipath Channel Environment

In the field of array signal processing, direction of arrival (DOA) estimation is a prime area of research. DOA estimation and adaptive beamforming (ABF) are the main issues in smart antennas, which dynamically find the direction of desired and interfering users and finds the optimum weights for beamforming. There are numerous spectral and eigen structure algorithms for estimating the direction of narrow band sources. However, in a complex multipath channel environment, received signals from different directions are fully or partially correlated, which prevents the applications of high resolution techniques to estimate the direction of incoming signals. Maximum likelihood (ML) is an efficient technique for DOA estimation in a low signal to noise ratio (SNR) and coherent channel environment. In this paper, we use particle swarm optimization (PSO) for estimating ML solution by optimizing complex non linear multimodal function over a high dimensional space in linear arrays. PSO-ML estimator has been compared with conventional DOA estimation techniques in uncorrelated, partially correlated and coherent channel environment. The performance of PSO-ML estimator and conventional algorithms are analyzed in varying partially correlated channel environment. The simulation results demonstrate that PSO based estimator gives superior statistical performance.     

Reliable Satellite Communications for a Specular Multipath Channel

In many mobile satellite communication systems specular multipath exists and acts as a distortion to the transmitted message stream. In most cases there is a singular specular return which can be characterized by a delay and reflection coefficient. If this return is viewed as intersymbol interference on the channel, then it is possible to consider the resulting channel as modeled by a finite state machine and process the received data stream optimally using the Viterbi algorithm. This paper develops such a scheme and derives a performance bound. A suboptimum scheme is also developed which is less sensitive to inaccurate knowledge of the multipath parameters. Performance bounds for the suboptimum scheme are also developed.     

An Improved Statistics Fingerprint Analysis Method for Time Delay Estimation in Multipath NLOS Environment

Wireless Personal Communications - This paper focuses on time of arrival (TOA) measurement for wireless personal area network (WPAN) under the circumstances that dense multipath and non-line of...