Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matri...Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matrix and filter parameters are difficult to be determined,which may result in filtering divergence.As to the problem that the accuracy of state estimation for nonlinear ballistic model strongly depends on its mathematical model,we improve the weighted least squares method(WLSM)with minimum model error principle.Invariant embedding method is adopted to solve the cost function including the model error.With the knowledge of measurement data and measurement error covariance matrix,we use gradient descent algorithm to determine the weighting matrix of model error.The uncertainty and linearization error of model are recursively estimated by the proposed method,thus achieving an online filtering estimation of the observations.Simulation results indicate that the proposed recursive estimation algorithm is insensitive to initial conditions and of good robustness.展开更多
Performance of the Adaptive Coding and Modulation(ACM) strongly depends on the retrieved Channel State Information(CSI),which can be obtained using the channel estimation techniques relying on pilot symbol transmissio...Performance of the Adaptive Coding and Modulation(ACM) strongly depends on the retrieved Channel State Information(CSI),which can be obtained using the channel estimation techniques relying on pilot symbol transmission.Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little.In this paper,we investigate the performance of CSI prediction using the Minimum Mean Square Error(MMSE)channel estimator for an ACM system.To solve the two problems of MMSE:high computational operations and oversimplified assumption,we then propose the Low-Complexity schemes(LC-MMSE and Recursion LC-MMSE(R-LC-MMSE)).Computational complexity and Mean Square Error(MSE) are presented to evaluate the efficiency of the proposed algorithm.Both analysis and numerical results show that LC-MMSE performs close to the wellknown MMSE estimator with much lower complexity and R-LC-MMSE improves the application of MMSE estimation to specific circumstances.展开更多
The L<sub>1</sub> regression is a robust alternative to the least squares regression whenever there are outliers in the values of the response variable, or the errors follow a long-tailed distribution. To ...The L<sub>1</sub> regression is a robust alternative to the least squares regression whenever there are outliers in the values of the response variable, or the errors follow a long-tailed distribution. To calculate the standard errors of the L<sub>1</sub> estimators, construct confidence intervals and test hypotheses about the parameters of the model, or to calculate a robust coefficient of determination, it is necessary to have an estimate of a scale parameterτ. This parameter is such that τ<sup>2</sup>/n is the variance of the median of a sample of size n from the errors distribution. [1] proposed the use of , a consistent, and so, an asymptotically unbiased estimator of τ. However, this estimator is not stable in small samples, in the sense that it can increase with the introduction of new independent variables in the model. When the errors follow the Laplace distribution, the maximum likelihood estimator of τ, say , is the mean absolute error, that is, the mean of the absolute residuals. This estimator always decreases when new independent variables are added to the model. Our objective is to develop asymptotic properties of under several errors distributions analytically. We also performed a simulation study to compare the distributions of both estimators in small samples with the objective to establish conditions in which is a good alternative to for such situations.展开更多
In this letter,by employing Gaussian distribution to approximate the probability density function(pdf) of the extrinsic information at the output of the multiuser detector as a function of the pdf of the input extrins...In this letter,by employing Gaussian distribution to approximate the probability density function(pdf) of the extrinsic information at the output of the multiuser detector as a function of the pdf of the input extrinsic messages,it is concluded that the Probabilistic Data Association(PDA) algorithm is equivalent to the Soft Interference Cancellation plus Minimum Mean Square Error algo-rithm(SIC-MMSE) .展开更多
The detection performance is evaluated for our proposed analog multiuser receiver in Ultra-WideBand (UWB) transmitted-reference system. In the presence of dense multipath and multi-access signals,the performance analy...The detection performance is evaluated for our proposed analog multiuser receiver in Ultra-WideBand (UWB) transmitted-reference system. In the presence of dense multipath and multi-access signals,the performance analysis is difficult due to the complicated waveform of received impulse. We develop an approach to analyze the steady-state Signal-to-Interference-plus-Noise (SINR) of the detector output. The multipath-spread impulse is fitted to an exponentially decaying profile in the analysis. A closed-form expression of steady-state SINR is further deduced for the proposed Least Minimum Square (LMS) detector. The analysis is validated by simulations in Line-Of-Sight (LOS) and Non-Line-Of-Sight (NLOS) channel respectively. Based on the theoretical results,the multipath delay spread is employed to determine the optimal width of the integration window of the detector.展开更多
The turbo equalization approach is studied for Orthogonal Frequency Division Multiplexing (OFDM) system with combined error control coding and linear precoding. While previous literatures employed linear precoder of s...The turbo equalization approach is studied for Orthogonal Frequency Division Multiplexing (OFDM) system with combined error control coding and linear precoding. While previous literatures employed linear precoder of small size for complexity reasons, this paper proposes to use a linear precoder of size larger than or equal to the maximum length of the equivalent discrete-time channel in order to achieve full frequency diversity and reduce complexities of the error control coder/decoder. Also a low complexity Linear Minimum Mean Square Error (LMMSE) turbo equalizer is derived for the receiver. Through simulation and performance analysis, it is shown that the performance of the proposed scheme over frequency selective fading channel reaches the matched filter bound; compared with the same coded OFDM without linear precoding, the proposed scheme shows an Signal-to-Noise Ratio (SNR) improvement of at least 6dB at a bit error rate of 10-6 over a multipath channel with exponential power delay profile. Convergence behavior of the proposed scheme with turbo equalization using various type of linear precoder/transformer, various inter-leaver size and error control coder of various constraint length is also investigated.展开更多
针对现有的正交频分享用(OFDM)网络信号接收过程中存在带外杂波扩散严重、信号投影难以匹配以及误码率较高等难题,提出了基于梯度映射机制的子载波OFDM网络信号精确接收算法。首先,通过快速傅里叶变换及其逆变换,并联合插值技术,构建最...针对现有的正交频分享用(OFDM)网络信号接收过程中存在带外杂波扩散严重、信号投影难以匹配以及误码率较高等难题,提出了基于梯度映射机制的子载波OFDM网络信号精确接收算法。首先,通过快速傅里叶变换及其逆变换,并联合插值技术,构建最小均方差预估抑制机制,并采用带通滤波技术对带外杂波进行全频域消除;随后,基于实部及虚部信号的数字特征,构建梯度映射机制,对信号投影点与投影象限进行匹配,降低OFDM网络误码率。仿真实验表明,与当前幅度滤波限制算法(amplitude filter algorithm,AF)、中波带频率抑制算法(wave band frequency suppression algorithm,WBFS)相比,所提算法具有更低的误码率,分别降低了2个、3个量级,以及更高的信号增益强度,在莱斯信道条件下,分别提高了20.5%、41.63%,且功率谱性能与理想状态下的OFDM信号最为接近。所提算法具有理想的信号接收精度与抗衰落性能,具有一定的实际部署价值。展开更多
为了降低正交频分复用OFDM(Orthogonal Frequency division Multiplexing)系统中最小均方误差MMSE(Minimum Mean Square Error)信道估计算法的复杂度,并且改善由于信道的统计特性与先验知识不匹配而导致的MMSE估计性能恶化,提出了一种...为了降低正交频分复用OFDM(Orthogonal Frequency division Multiplexing)系统中最小均方误差MMSE(Minimum Mean Square Error)信道估计算法的复杂度,并且改善由于信道的统计特性与先验知识不匹配而导致的MMSE估计性能恶化,提出了一种自适应的低秩信道估计算法.该算法利用信道的时间平均相关取代统计相关,结合了基于特征值分解的低秩建模,从而近似地实现MMSE估计.借助于子空间跟踪,该算法可以自适应地估计信道相关矩阵的主特征空间及噪声方差,以迭代的方式逼近最优的MMSE估计,而且复杂度较低.进一步分析指出基于信道延时子空间跟踪的估计算法是该算法的一种特例,理论分析和仿真结果均表明这种新算法在低信噪比时可以显著改善信道估计的准确性.展开更多
正交频分复用技术在无线通信系统中应用十分广泛,可有效对抗信号符号间干扰,适用于多径和衰落信道中的高速数据传输。为提高通信传输质量,需要对信道脉冲响应值进行估计。基于块状导频的估计算法有最小二乘(Least Square,LS)估计、最小...正交频分复用技术在无线通信系统中应用十分广泛,可有效对抗信号符号间干扰,适用于多径和衰落信道中的高速数据传输。为提高通信传输质量,需要对信道脉冲响应值进行估计。基于块状导频的估计算法有最小二乘(Least Square,LS)估计、最小均方误差(Minimum Mean Square Error,MMSE)估计、线性最小均方误差(Linear Minimum Mean Square Error,LMMSE)估计和基于特征值分解(Singular Value Decomposition,SVD)的估计算法。根据仿真结果比较了4种算法的误符号率性能及算法的复杂性。在相同信噪比条件下,MMSE算法误符号率最低,但算法复杂度最高,计算耗时最长;LS算法计算简单,耗时最短,但误符号率最高;LMMSE和SVD算法复杂度比MMSE低,耗时明显减小,同时对信道估计的准确性比MMSE算法稍有下降。展开更多
基金This work is supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX18_0467)Jiangsu Province,China.During the revision of this paper,the author is supported by China Scholarship Council(No.201906840021)China to continue some research related to data processing.
文摘Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matrix and filter parameters are difficult to be determined,which may result in filtering divergence.As to the problem that the accuracy of state estimation for nonlinear ballistic model strongly depends on its mathematical model,we improve the weighted least squares method(WLSM)with minimum model error principle.Invariant embedding method is adopted to solve the cost function including the model error.With the knowledge of measurement data and measurement error covariance matrix,we use gradient descent algorithm to determine the weighting matrix of model error.The uncertainty and linearization error of model are recursively estimated by the proposed method,thus achieving an online filtering estimation of the observations.Simulation results indicate that the proposed recursive estimation algorithm is insensitive to initial conditions and of good robustness.
基金supported by the 2011 China Aerospace Science and Technology Foundationthe Certain Ministry Foundation under Grant No.20212HK03010
文摘Performance of the Adaptive Coding and Modulation(ACM) strongly depends on the retrieved Channel State Information(CSI),which can be obtained using the channel estimation techniques relying on pilot symbol transmission.Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little.In this paper,we investigate the performance of CSI prediction using the Minimum Mean Square Error(MMSE)channel estimator for an ACM system.To solve the two problems of MMSE:high computational operations and oversimplified assumption,we then propose the Low-Complexity schemes(LC-MMSE and Recursion LC-MMSE(R-LC-MMSE)).Computational complexity and Mean Square Error(MSE) are presented to evaluate the efficiency of the proposed algorithm.Both analysis and numerical results show that LC-MMSE performs close to the wellknown MMSE estimator with much lower complexity and R-LC-MMSE improves the application of MMSE estimation to specific circumstances.
文摘The L<sub>1</sub> regression is a robust alternative to the least squares regression whenever there are outliers in the values of the response variable, or the errors follow a long-tailed distribution. To calculate the standard errors of the L<sub>1</sub> estimators, construct confidence intervals and test hypotheses about the parameters of the model, or to calculate a robust coefficient of determination, it is necessary to have an estimate of a scale parameterτ. This parameter is such that τ<sup>2</sup>/n is the variance of the median of a sample of size n from the errors distribution. [1] proposed the use of , a consistent, and so, an asymptotically unbiased estimator of τ. However, this estimator is not stable in small samples, in the sense that it can increase with the introduction of new independent variables in the model. When the errors follow the Laplace distribution, the maximum likelihood estimator of τ, say , is the mean absolute error, that is, the mean of the absolute residuals. This estimator always decreases when new independent variables are added to the model. Our objective is to develop asymptotic properties of under several errors distributions analytically. We also performed a simulation study to compare the distributions of both estimators in small samples with the objective to establish conditions in which is a good alternative to for such situations.
文摘In this letter,by employing Gaussian distribution to approximate the probability density function(pdf) of the extrinsic information at the output of the multiuser detector as a function of the pdf of the input extrinsic messages,it is concluded that the Probabilistic Data Association(PDA) algorithm is equivalent to the Soft Interference Cancellation plus Minimum Mean Square Error algo-rithm(SIC-MMSE) .
基金Supported by the Guangxi Natural Science Foundation (No.0731025, No.0731026)the Established Project by Guangxi Education Department (No.200808LX117)
文摘The detection performance is evaluated for our proposed analog multiuser receiver in Ultra-WideBand (UWB) transmitted-reference system. In the presence of dense multipath and multi-access signals,the performance analysis is difficult due to the complicated waveform of received impulse. We develop an approach to analyze the steady-state Signal-to-Interference-plus-Noise (SINR) of the detector output. The multipath-spread impulse is fitted to an exponentially decaying profile in the analysis. A closed-form expression of steady-state SINR is further deduced for the proposed Least Minimum Square (LMS) detector. The analysis is validated by simulations in Line-Of-Sight (LOS) and Non-Line-Of-Sight (NLOS) channel respectively. Based on the theoretical results,the multipath delay spread is employed to determine the optimal width of the integration window of the detector.
基金Supported by the National High Technology ResearchDevelopment Program of China (863 Program)(No.2001AA 123014)
文摘The turbo equalization approach is studied for Orthogonal Frequency Division Multiplexing (OFDM) system with combined error control coding and linear precoding. While previous literatures employed linear precoder of small size for complexity reasons, this paper proposes to use a linear precoder of size larger than or equal to the maximum length of the equivalent discrete-time channel in order to achieve full frequency diversity and reduce complexities of the error control coder/decoder. Also a low complexity Linear Minimum Mean Square Error (LMMSE) turbo equalizer is derived for the receiver. Through simulation and performance analysis, it is shown that the performance of the proposed scheme over frequency selective fading channel reaches the matched filter bound; compared with the same coded OFDM without linear precoding, the proposed scheme shows an Signal-to-Noise Ratio (SNR) improvement of at least 6dB at a bit error rate of 10-6 over a multipath channel with exponential power delay profile. Convergence behavior of the proposed scheme with turbo equalization using various type of linear precoder/transformer, various inter-leaver size and error control coder of various constraint length is also investigated.
文摘针对现有的正交频分享用(OFDM)网络信号接收过程中存在带外杂波扩散严重、信号投影难以匹配以及误码率较高等难题,提出了基于梯度映射机制的子载波OFDM网络信号精确接收算法。首先,通过快速傅里叶变换及其逆变换,并联合插值技术,构建最小均方差预估抑制机制,并采用带通滤波技术对带外杂波进行全频域消除;随后,基于实部及虚部信号的数字特征,构建梯度映射机制,对信号投影点与投影象限进行匹配,降低OFDM网络误码率。仿真实验表明,与当前幅度滤波限制算法(amplitude filter algorithm,AF)、中波带频率抑制算法(wave band frequency suppression algorithm,WBFS)相比,所提算法具有更低的误码率,分别降低了2个、3个量级,以及更高的信号增益强度,在莱斯信道条件下,分别提高了20.5%、41.63%,且功率谱性能与理想状态下的OFDM信号最为接近。所提算法具有理想的信号接收精度与抗衰落性能,具有一定的实际部署价值。
文摘为了降低正交频分复用OFDM(Orthogonal Frequency division Multiplexing)系统中最小均方误差MMSE(Minimum Mean Square Error)信道估计算法的复杂度,并且改善由于信道的统计特性与先验知识不匹配而导致的MMSE估计性能恶化,提出了一种自适应的低秩信道估计算法.该算法利用信道的时间平均相关取代统计相关,结合了基于特征值分解的低秩建模,从而近似地实现MMSE估计.借助于子空间跟踪,该算法可以自适应地估计信道相关矩阵的主特征空间及噪声方差,以迭代的方式逼近最优的MMSE估计,而且复杂度较低.进一步分析指出基于信道延时子空间跟踪的估计算法是该算法的一种特例,理论分析和仿真结果均表明这种新算法在低信噪比时可以显著改善信道估计的准确性.
文摘正交频分复用技术在无线通信系统中应用十分广泛,可有效对抗信号符号间干扰,适用于多径和衰落信道中的高速数据传输。为提高通信传输质量,需要对信道脉冲响应值进行估计。基于块状导频的估计算法有最小二乘(Least Square,LS)估计、最小均方误差(Minimum Mean Square Error,MMSE)估计、线性最小均方误差(Linear Minimum Mean Square Error,LMMSE)估计和基于特征值分解(Singular Value Decomposition,SVD)的估计算法。根据仿真结果比较了4种算法的误符号率性能及算法的复杂性。在相同信噪比条件下,MMSE算法误符号率最低,但算法复杂度最高,计算耗时最长;LS算法计算简单,耗时最短,但误符号率最高;LMMSE和SVD算法复杂度比MMSE低,耗时明显减小,同时对信道估计的准确性比MMSE算法稍有下降。
