A new multi-sensor data fusion algorithm based on EMD-MMSE was proposed.Empirical mode decomposition(EMD)is used to extract the noise of every time series for estimating the variance of the noise.Then minimum mean squ...A new multi-sensor data fusion algorithm based on EMD-MMSE was proposed.Empirical mode decomposition(EMD)is used to extract the noise of every time series for estimating the variance of the noise.Then minimum mean square error(MMSE)estimator is used to calculate the weights of the corresponding series.Finally,the fused signal is the weighted addition of all these series.The experiments in lab testified the efficiency of this method.In addition,the comparison in fusion time and fusion results with existing fusion method based on wavelet and average technique shows the advantage of this method greatly.展开更多
The unknown parameter’s variance-covariance propagation and calculation in the generalized nonlinear least squares remain to be studied now, which didn’t appear in the internal and external referencing documents. Th...The unknown parameter’s variance-covariance propagation and calculation in the generalized nonlinear least squares remain to be studied now, which didn’t appear in the internal and external referencing documents. The unknown parameter’s vari- ance-covariance propagation formula, considering the two-power terms, was concluded used to evaluate the accuracy of unknown parameter estimators in the generalized nonlinear least squares problem. It is a new variance-covariance formula and opens up a new way to evaluate the accuracy when processing data which have the multi-source, multi-dimensional, multi-type, multi-time-state, different accuracy and nonlinearity.展开更多
Many applications require the solution of large nonsymmetric linear systems with multiple right hand sides. Instead of applying an iterative method to each of these systems individually, it is often more efficient to...Many applications require the solution of large nonsymmetric linear systems with multiple right hand sides. Instead of applying an iterative method to each of these systems individually, it is often more efficient to use a block version of the method that generates iterates for all the systems simultaneously. In this paper, we propose a block version of generalized minimum backward (GMBACK) for solving large multiple nonsymmetric linear systems. The new method employs the block Arnoldi process to construct a basis for the Krylov subspace K m(A, R 0) and seeks X m∈X 0+K m(A, R 0) to minimize the norm of the perturbation to the data given in A.展开更多
The paper deals with two-dimensional （2D） channel estimation of Orthogonal Frequency Division Multiplexing （OFDM） system ill slow fading wireless channel. We concentrate on two channel estimation schemes： Least S...The paper deals with two-dimensional （2D） channel estimation of Orthogonal Frequency Division Multiplexing （OFDM） system ill slow fading wireless channel. We concentrate on two channel estimation schemes： Least Square （LS）＋Weighted BiLinear （WBL） and LS＋Linear Minimum Mean-Squared Error （LMMSE） where the first method is proposed in this paper. After theory analysis and simulation in Typical Urban （TU） channel, we find that LS＋LMMSE achieves the optimal perform- anee by exploiting prior knowledge of channel whereas LS＋WBL, without requiring channel knowl- edge and with only half of the computational amount of LS＋LMMSE, approaches LS＋LMMSE in Bit Error Ratio （BER） performance when the distance of two adjoining pilot symbols along frequency direction is sufficiently small. This makes LS＋WBL very suitable for wideband wireless applications.展开更多
Orthogonal Frequency Division Multiplexing(OFDM) is an effective technique to deal with a frequency selective channel since it can convert the channel into some flat fading subchannels.However,very different output SN...Orthogonal Frequency Division Multiplexing(OFDM) is an effective technique to deal with a frequency selective channel since it can convert the channel into some flat fading subchannels.However,very different output SNR values of the subchannels will lead to poor bit error performance when a linear equalizer and Equal Bit Allocation(EBA) are adopted in OFDM systems.So,we proposed three novel nonlinear Joint Transceiver(JT) schemes based on Zero-Forcing(ZF) criterion and Minimum Mean Square Error(MMSE) criterion respectively,which can transform all subchannels of an OFDM system into subchannels with identical channel gain.Thus,EBA is equivalent to the Optimum Bit Allocation(OBA) for these subchannels.Numerical analysis helps us to obtain the theoretical approximate BER values of the JT scheme.Simulation results verify the numerical analysis and confirm that the performance of our proposed JT scheme greatly outperforms the traditional linear equalizer with EBA at moderate and high SNR values.展开更多
A simplified minimum mean square error(MMSE) detector is proposed for joint detection and decoding of multi-ple-input multiple-output(MIMO) systems.The matrix inversion lemma and the singular value decomposition(SVD) ...A simplified minimum mean square error(MMSE) detector is proposed for joint detection and decoding of multi-ple-input multiple-output(MIMO) systems.The matrix inversion lemma and the singular value decomposition(SVD) of the channel matrix are used to simplify the computation of the coefficient of the MMSE filter.Compared to the original MMSE detector,the proposed detector has a much lower computational complexity with only a marginal performance loss.The proposed detector can also be applied to MIMO systems with high order modulations.展开更多
基金The National High Technology Research and Development Program of China(863Program)(No.2001AA602021)
文摘A new multi-sensor data fusion algorithm based on EMD-MMSE was proposed.Empirical mode decomposition(EMD)is used to extract the noise of every time series for estimating the variance of the noise.Then minimum mean square error(MMSE)estimator is used to calculate the weights of the corresponding series.Finally,the fused signal is the weighted addition of all these series.The experiments in lab testified the efficiency of this method.In addition,the comparison in fusion time and fusion results with existing fusion method based on wavelet and average technique shows the advantage of this method greatly.
基金Supported by the National Natural Science Foundation of China (40174003)
文摘The unknown parameter’s variance-covariance propagation and calculation in the generalized nonlinear least squares remain to be studied now, which didn’t appear in the internal and external referencing documents. The unknown parameter’s vari- ance-covariance propagation formula, considering the two-power terms, was concluded used to evaluate the accuracy of unknown parameter estimators in the generalized nonlinear least squares problem. It is a new variance-covariance formula and opens up a new way to evaluate the accuracy when processing data which have the multi-source, multi-dimensional, multi-type, multi-time-state, different accuracy and nonlinearity.
文摘Many applications require the solution of large nonsymmetric linear systems with multiple right hand sides. Instead of applying an iterative method to each of these systems individually, it is often more efficient to use a block version of the method that generates iterates for all the systems simultaneously. In this paper, we propose a block version of generalized minimum backward (GMBACK) for solving large multiple nonsymmetric linear systems. The new method employs the block Arnoldi process to construct a basis for the Krylov subspace K m(A, R 0) and seeks X m∈X 0+K m(A, R 0) to minimize the norm of the perturbation to the data given in A.
基金Supported by the National Natural Science Foundation of China (No: 60496311).
文摘The paper deals with two-dimensional （2D） channel estimation of Orthogonal Frequency Division Multiplexing （OFDM） system ill slow fading wireless channel. We concentrate on two channel estimation schemes： Least Square （LS）＋Weighted BiLinear （WBL） and LS＋Linear Minimum Mean-Squared Error （LMMSE） where the first method is proposed in this paper. After theory analysis and simulation in Typical Urban （TU） channel, we find that LS＋LMMSE achieves the optimal perform- anee by exploiting prior knowledge of channel whereas LS＋WBL, without requiring channel knowl- edge and with only half of the computational amount of LS＋LMMSE, approaches LS＋LMMSE in Bit Error Ratio （BER） performance when the distance of two adjoining pilot symbols along frequency direction is sufficiently small. This makes LS＋WBL very suitable for wideband wireless applications.
基金the National Natural Science Foundation of China for Distinguished Young Scholars，the National Key Basic Research Program of China (973 program)，the National Natural Science Foundation of China，the National Science and Technology Major Project，the Special Research Fund of State Key Laboratory，the 111 Project
文摘Orthogonal Frequency Division Multiplexing(OFDM) is an effective technique to deal with a frequency selective channel since it can convert the channel into some flat fading subchannels.However,very different output SNR values of the subchannels will lead to poor bit error performance when a linear equalizer and Equal Bit Allocation(EBA) are adopted in OFDM systems.So,we proposed three novel nonlinear Joint Transceiver(JT) schemes based on Zero-Forcing(ZF) criterion and Minimum Mean Square Error(MMSE) criterion respectively,which can transform all subchannels of an OFDM system into subchannels with identical channel gain.Thus,EBA is equivalent to the Optimum Bit Allocation(OBA) for these subchannels.Numerical analysis helps us to obtain the theoretical approximate BER values of the JT scheme.Simulation results verify the numerical analysis and confirm that the performance of our proposed JT scheme greatly outperforms the traditional linear equalizer with EBA at moderate and high SNR values.
文摘A simplified minimum mean square error(MMSE) detector is proposed for joint detection and decoding of multi-ple-input multiple-output(MIMO) systems.The matrix inversion lemma and the singular value decomposition(SVD) of the channel matrix are used to simplify the computation of the coefficient of the MMSE filter.Compared to the original MMSE detector,the proposed detector has a much lower computational complexity with only a marginal performance loss.The proposed detector can also be applied to MIMO systems with high order modulations.
