一种改进LS信道估计算法在稀疏多径水声信道中的应用

为了消除水声正交频分复用调制(Orthogonal Frequency Division Multiplexing,OFDM)系统中噪声对稀疏多径信道估计的影响,提出了一种改进的最小二乘(Least-Square,LS)信道估计算法。该方法在传统基于离散傅里叶变换(Discrete Fourier Transform,DFT)插值的信道估计结构上进行了改进,得到了基于阈值探测的DFT插值信道估计方法,该方法将小于阈值的时域信道响应置零,探测最有效信道抽头,有效消除噪声干扰的影响。仿真结果验证了DFT插值在稀疏多径水声信道估计中的实用性;得到了当循环前缀长度与信道长度越接近时信道估计性能(Bit Error Rate,BER)越好的结论;确定了在两种调制方式下算法的阈值系数范围;且该新算法与已有算法所需的信噪比可低约2 d B,解决了用循环前缀长度来近似信道真实长度的实际问题。     

大气光通信中Turbo码的最大后验概率译码

为了精确实现对空间物体的测量,提出了利用线激光、单CCD相机、小孔成像与激光面约束模型的激光线测量法。引进三维信息已知的标准阶梯块作为激光面约束的标定块;由计算机控制摄像头对实物连续拍摄和实时处理,提取激光线上的像素坐标;利用建立的模型将二维坐标转换成三维坐标,再以点云的形式重构出物体,实现三维自动测量。实践中检测系统测量精度可达到0.05mm。     

Concatenated coded modulation techniques and orthogonal space-time block codes in the presence of fading channel estimation errors

Performance of coding and modulation systems in fading channels is usually analysed under the assumption that the receiver has perfect knowledge of channel condition. However, various shortcomings in practical channel estimation techniques lead to imperfections, resulting in channel estimation errors. The authors analyse a practical coding and modulation scheme for multiple-antenna systems considering channel estimation errors. The novelty of this study resides in providing error probability bounds for concatenated trellis coded modulation (TCM) or bit-interleaved coded modulation (BICM) schemes with orthogonal space--time block codes (OSTBC) under imperfect channel estimation assumption. Moreover, our analytical results quantify the performance degradation associated with various levels of channel estimation error variance. The authors also show that if channel estimation quality does not improve sufficiently with SNR, there would be error floor in performance, such that the coded system could get outperformed by a system with differential signalling that requires no channel estimation. Simulation results are presented, which confirm the validity of the analytical results.     

无线城域网OFDM系统信道估计算法

OFDM技术是无线城域网IEEE802.16a标准中物理层面的主流调制技术,今建立符合IEEE802.16a标准的OFDM信道估计模型,阐述其导频基本信道估计方法的原理及特点,分析比较了LS/MMSE/LMMSE/SVD四种算法的MSE和BER性能特点.仿真结果说明,LMMSE算法的均方误差和误码率性能最好,且计算复杂度相对较低,易于物理实现.     

基于压缩感知的多中继协作通信系统稀疏信道估计算法研究

提出了一种基于压缩感知理论的多中继协作通信系统稀疏信道估计方法.采用正交匹配追踪（Orthogonal Matching Pursuit,OMP）压缩感知算法,对时域信道脉冲响应进行估计.对多中继协作通信系统进行稀疏建模;结合压缩感知理论构建观测矩阵,并给出卷积信道的稀疏表示;利用压缩信道感知算法重建了系统的卷积复合信道.仿真结果表明,与传统的最小二乘法（Least Square,LS）相比,采用压缩感知理论的信道估计算法,能利用较少的导频信号获得很好的信道估计性能,提高了频谱利用率.     

基于差分进化的时变信道最大似然估计算法

研究了隧道环境下的通信信道估计。针对隧道环境的地铁列车与轨旁设备之间无线通信中无线传输信道快速变化的特点,提出了一种采用元胞差分进化(DE)方法实时获取时变信道的有效信道长度的新型最大似然(ML)信道估计算法——DE-ML算法。仿真结果表明该算法在使用较少导频信息的情况下,通过差分进化方法有效估计跟踪有效信道长度,其估计性能优于最小二乘(LS)、线性最小均方误差(LMMSE)、传统ML等经典信道估计算法。该算法能在提高系统传输效率的同时显著提高算法的估计精度,尤其在高速移动情况下也具有了非常良好的性能。     

Semi-blind channel estimation for the uplink of multi-carrier code-division multiple access systems with timing offset

Timing offsets (TO) introduce misaligned interferences and phase errors, which degrade the performance of channel estimation. The authors propose a new semi-blind channel estimator that can cancel the TO effects on channel estimation and work well in the uplink of multi-carrier code-division multiple access systems in the presence of TO. The proposed channel estimator exploits the spreading sequence information instead of pilots to accomplish semi-blind estimation. Since the estimated channel coefficients are affected by the users? transmitted data, the effect of the users? data needs to be reduced. For this purpose, the authors also propose two smoothing algorithms, division smoothing and optimisation smoothing. In addition, to extend the new estimator to the system where the number of active users is too large, channel estimation over multiple symbols is discussed. The simulation results show that the proposed semi-blind estimator works better than a conventional estimator in the presence of TO, and its performance is very close to the conventional estimator in the absence of TO. Besides, the proposed estimator is compared with a sub-space estimator in simulation, and the results indicate that the new proposed estimator can achieve the same mean square error performance over the duration of a single symbol as the sub-space estimator over the duration of several symbols.     

适用于OFDM系统的改进的信道估计算法

针对实际系统中的信道冲激响应(CIR)泄漏问题,提出了一种适用于梳状导频正交频分复用(OFDM)系统的改进的最小二乘(LS)信道估计算法.该算法基于分数抽头延时信道近似(FTCA)的参数化信道模型,此信道模型采用一个抽头间隔为分数倍采样间隔的抽头延时线结构的有限冲激响应(FIR)滤波器表示.此算法首先通过FTCA信道模型来近似实际信道,然后再估计该信道模型中的某些参数来获取实际的信道信息;该算法利用了FTCA信道模型中所有的延时抽头,从而很好地抑制了CIR泄漏.仿真与分析表明,FTCA信道模型能够有效地近似实际信道,同时降低信道自相关矩阵的维数,从而提高信道估计的性能.     

Decision-directed channel estimation based on iterative linear minimum mean square error for orthogonal frequency division multiplexing systems

A decision-directed (DD) channel estimation based on iterative linear minimum mean square error (LMMSE) is proposed for orthogonal frequency division multiplexing systems. Existing DD channel estimation is well known to have the problem of error propagation because of symbol-by-symbol detection. The proposed algorithm can estimate the correction term of current channel state information (CSI) according to the error vector of previous CSI by applying the orthogonality principle, and corrects the current CSI with this correction term. Analysis and simulation results have shown that this method has no error propagation problem. The performance of the proposed algorithm is much better than the conventional DD channel estimation, and close to the optimal LMMSE estimator, but with much less computational complexity compared with the optimal LMMSE estimator.     

基于有效抽头和进化规划算法的自适应水声信道估计

为了实现稀疏水声信道的快速高效估计,提出一种新的基于有效抽头的信道参数模型降低运算复杂性,并采用进化算法以最小二乘误差为适应度函数对信道响应中有效抽头的阶数、位置和权重同时进行进化操作寻优,避免了有色输入造成的相邻抽头耦合导致的性能下降。仿真实验结果表明:与传统LMS算法及基于有效抽头检测的稀疏信道估计方法相比,该算法在有色输入信号下具有更优越的估计性能和收敛速度,为稀疏水声信道处理提供了一类新方法。     

Optimal power and subcarriers allocation in downlink OFDMA system with imperfect channel knowledge

Most of existing work on resource allocation in TDMA and OFDMA systems assumes the availability of perfect channel state information (CSI) at the transmitter, which is rarely possible due to feedback delay and channel estimation error. In this paper, we study the effect of feedback delay and channel estimation error on margin adaptive resource allocation in a downlink OFDMA system. By using convex optimization framework, we find an optimal solution to the problem. First, we study the individual effect of feedback delay and channel estimation error on resource allocation by considering them exclusively. Then, we consider the simultaneous presence of feedback delay and channel estimation error and study their combined effect on resource allocation. We derive an explicit close form expression for the users’ transmit power and propose an algorithm for power and subcarriers allocation for each of these three scenarios. The algorithms have polynomial complexities and solve the problem with zero optimality gaps. Simulation results show that the system performance is very sensitive to feedback delay and is affected significantly by imperfect channel estimation. Our proposed algorithms highly improve the system performance in the availability of only imperfect CSI at the transmitter.     

Error-reduction techniques and error analysis for fully phase- and amplitude-based encryption

The performance of fully phase- and amplitude-based encryption processors is analyzed. The effects of noise perturbations on the encrypted information are considered. A thresholding method of decryption that further reduces the mean-squared error (MSE) for the fully phase- and amplitude-based encryption processes is provided. The proposed thresholding scheme significantly improves the performance of fully phase- and amplitude-based encryption, as measured by the MSE metric. We obtain analytical MSE bounds when thresholding is used for both decryption methods, and we also present computer-simulation results. These results show that the fully phase-based method is more robust. We also give a formal proof of a conjecture about the decrypted distribution of distorted encrypted information. This allows the analytical bounds of the MSE to be extended to more general non-Gaussian, nonadditive, nonstationary distortions. Computer simulations support this extension.     

基于卡尔曼滤波的时变水声信道估计

为了能同时利用时变水声信道的簇状稀疏特性和时间相关性,构造了一种时变水声信道模型,并基于该模型对传统的卡尔曼滤波压缩感知算法进行改进。该方法主要利用前一时刻估计的信道状态响应来确定当前时刻信道的候选支撑集,并以此构造时变水声信道的状态转移方程。通过卡尔曼滤波迭代的方法计算候选支撑集上的系数,最后通过阈值法滤除误差原子。仿真结果表明：该方法能有效地利用水声信道间的时间相关性来提高信道估计的性能,同时由于水声信道存在簇状稀疏特性,因此经该方法也具有一定的鲁棒性。     

High mobility orthogonal frequency division multiple access channel estimation using basis expansion model

Owing to the loss of subcarrier orthogonalities in high-speed applications, the use of conventional frequency-domain-based channel estimation in high mobility orthogonal frequency division multiple access (OFDMA) systems such as mobile WiMax may give rise to an unacceptable high channel estimation error floor. To alleviate this problem, the authors develop some basis expansion model (BEM)-based estimation schemes for the OFDMA uplink. Specifically, the authors express the time-varying channel as a superposition of a small number of complex exponential basis functions spanning the entire Doppler range, and then formulate least square (LS) and linear minimum mean square error (LMMSE) algorithms to estimate the basis coefficients for two different types of pilot patterns. The authors also derive the respective Cramer-Rao lower bounds for these estimators. It has been shown that the time domain BEM using a pilot scheme where pilots are placed over time axis will give better performance under a high Doppler scenario. Lastly, using simulation results, the proposed algorithms have been found to have better estimation accuracy over current frequency domain estimation techniques. This is in addition to the advantage that the proposed algorithms have in general a lower computational complexity.     

Artificial Intelligence in Material Engineering: A Review on Applications of Artificial Intelligence in Material Engineering

The role of artificial intelligence (AI) in material science and engineering (MSE) is becoming increasingly important as AI technology advances. The development of high-performance computing has made it possible to test deep learning (DL) models with significant parameters, providing an opportunity to overcome the limitation of traditional computational methods, such as density functional theory (DFT), in property prediction. Machine learning (ML)-based methods are faster and more accurate than DFT-based methods. Furthermore, the generative adversarial networks (GANs) have facilitated the generation of chemical compositions of inorganic materials without using crystal structure information. These developments have significantly impacted material engineering (ME) and research. Some of the latest developments in AI in ME herein are reviewed. First, the development of AI in the critical areas of ME, such as in material processing, the study of structure and material property, and measuring the performance of materials in various aspects, is discussed. Then, the significant methods of AI and their uses in MSE, such as graph neural network, generative models, transfer of learning, etc. are discussed. The use of AI to analyze the results from existing analytical instruments is also discussed. Finally, AI's advantages, disadvantages, and future in ME are discussed.     

基于gOMP算法的FBMC水声通信信道估计方法

传统基于训练序列及块状导频结构的滤波器组多载波（Filter Bank Multicarrier,FBMC）信道估计方法花费额外的频谱资源,这在频谱资源较为紧张的水声通信环境中具有一定的局限性。针对这一问题并结合水声信道稀疏性的特点,文章提出了一种基于压缩感知的离散导频结构FBMC信道估计方法。首先基于等效导频能量最大化的思想,设计了一种新的离散导频结构来解决FBMC系统信道估计时存在的固有虚部干扰问题;然后配合该结构,提取出导频处的接收信息并利用重构效果优良的压缩感知gOMP算法对水声信道进行重构。该方法在保证水声信道估计精度的同时有效提高了FBMC系统的频谱利用率,改善了水声通信的性能。仿真结果表明,文中所提方法相较于传统方法在估计精度和频谱利用率方面具有一定的优越性。     

基于深度神经网络的水声FBMC通信信号检测方法

针对传统水声滤波器组多载波（Filter Bank Multi-Carrier,FBMC）通信接收端需经过信道估计和均衡才可恢复出发送符号,系统复杂度高且信道估计精度不佳等问题。文章将深度神经网络融入到水声多载波通信当中,提出一种基于深度神经网络的水声FBMC信号检测方法。在训练阶段通过大量的数据迭代、调试超参数和优化算法来改善深度神经网络参数,使其具有预期的估计效果。利用训练完成的深度神经网络模型取代传统FBMC通信系统接收端的信道估计、均衡等模块,自适应地学习水声信道状态信息,同时避免了固有的虚部干扰影响。在测试阶段直接将频域序列作为网络的输入来预测发送的二进制序列,仿真结果表明所提出的基于深度神经网络的FBMC信号检测方法相比传统信道估计算法有更好的误码率性能。     

一种快速自适应噪声谱估计方法

提出了一种快速自适应的噪声谱估计方法。该方法在Doblinger和Cohen的噪声谱估计方法基础上,提出了改进算法,修正了带噪语音子带中语音存在的判断门限和噪声谱更新公式,估计的噪声谱既能快速适应背景噪声变化,又能保证准确性。实验结果表明,结合文中噪声谱估计方法构成的语音增强系统能有效抑制带噪语音中平稳和非平稳噪声,对于噪声突变的情况也适用。     

Maximum a posteriori channel estimation for cooperative diversity orthogonal frequencydivision multiplexing systems in amplify-andforward mode

Transmit diversity-orthogonal frequency-division multiplexing (OFDM) systems have been proposed to mitigate the detrimental effects of channel fading. However, owing to the space and power limitations, the use of multiple transmit antennas is not practical in certain wireless devices, such as portable terminals and wireless sensors. Therefore cooperation among users at the physical layer has been proposed recently. Here, space-time block coded in amplify-and-forward (AF) relaying mode has been proposed as cooperative diversity for OFDM systems (CO-OFDM) in the presence of perfect channel-state information. Then, the channel estimation techniques for CO-OFDM systems in AF mode based on pilot symbols are investigated over frequency-selective channels. In particular, expectation-maximisation (EM) based maximum a posteriori (MAP) channel estimation is developed and compared with comp-type pilot-aided channel estimation (PACE) based the maximum likelihood (ML) estimator and the least minimum mean-square error (LMMSE) channel estimation techniques for CO-OFDM systems. To overcome the drawback owing to the receiver complexity, the Karhunen-Loeve expansion with the optimal truncation property is also considered. Simulation results that demonstrate the overall performance advantage of the EM-MAP based receiver over the PACE-ML and PACE-LMMSE based receivers are presented.     

Channel estimation assisted by postfixed pseudo-noise sequences padded with zero samples for mobile orthogonal-frequency-division-multiplexing communications

A channel estimation (CE) technique that uses a postfixed pseudo-random sequence padded with zero samples is investigated to extend pseudo-random-postfix orthogonal-frequency-division-multiplexing (PRP-OFDM) communications onto mobile applications. The proposed technique takes advantage of pseudo-noise sequences periodically inserted after each OFDM block within the original guard interval (GI) in conventional zero-padded OFDM (ZP-OFDM) or within the original cyclic prefix (CP) in conventional CP-OFDM. This allows accurate estimation of the channel impulse response. In addition, the proposed technique takes advantage of the null samples padded after the PN sequences for reducing inter-symbol interference occurring with the CEs and with the overlap-add information detection in the conventional PRP-OFDM. The proposed technique successfully applies either (1) a least-squares (LS) CE with assistance from decision-directed data or (2) an approximate LS CE method onto PRP-OFDM-like communications for the purpose of improving CE performance on rapid time-varying channels. Computer simulations in conjunction with statistical analysis assess the performance evaluation of the proposed technique and show that it can achieve lower mean-square estimation errors and lower error probabilities in mobile environments.