Based on the fact that the variation of tile direction of arrival (DOA) isslower than that of the channel fading, the steering vector of the desired signal is estimatedfirstly using a subspace decomposition method and...Based on the fact that the variation of tile direction of arrival (DOA) isslower than that of the channel fading, the steering vector of the desired signal is estimatedfirstly using a subspace decomposition method and then a constrained condition is configured.Traffic signals are further employed to estimate the channel vector based on the constrained leastsquares criterion. We use the iterative least squares with projection (ILSP) algorithm initializedby the pilot to get the estimation. The accuracy of channel estimation and symbol detection can beprogressively increased through the iteration procedure of the ILSP algorithm. Simulation resultsdemonstrate that the proposed algorithm improves the system performance effectively compared withthe conventional 2-D RAKE receiver.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
A pilot pattern across two orthogonal frequency division multiplexing OFDM symbols with a special structure is designed for the channel estimation of OFDM systems with inphase and quadrature IQ imbalances at the recei...A pilot pattern across two orthogonal frequency division multiplexing OFDM symbols with a special structure is designed for the channel estimation of OFDM systems with inphase and quadrature IQ imbalances at the receiver.A high-efficiency time-domain TD least square LS channel estimator and a low-complexity frequency-domain Gaussian elimination GE equalizer are proposed to eliminate IQ distortion.The former estimator can significantly suppress channel noise by a factor N/L＋1 over the existing frequency-domain FD LS where N and L＋1 are the total number of subcarriers and the length of cyclic prefix and the proposed GE requires only 2N complex multiplications per OFDM symbol.Simulation results show that by exploiting the TD property of the channel the proposed TD-LS channel estimator obtains a significant signal-to-noise ratio gain over the existing FD-LS one whereas the proposed low-complexity GE compensation achieves the same bit error rate BER performance as the existing LS one.展开更多
Under analyzing several characteristics of frequency-selective fast fading channels, such as large Doppler spread and multi-path interference, a low-dimensional Kalman filter method based on pilot signals is presented...Under analyzing several characteristics of frequency-selective fast fading channels, such as large Doppler spread and multi-path interference, a low-dimensional Kalman filter method based on pilot signals is presented for the channel estimation of orthogonal frequency division multiplexing （OFDM） systems. For simplicity, a one-dimensional autoregressive （AR） process is used to model the time-varying channel, and the least square （LS） algorithm based on pilot signals is adopted to track the time-varying channel fading factor a. The low-dimensional Kalman filter estimator greatly reduces the complexity of the high-dimensional Kalman filter. To utilize the relationship of fading channel in frequency domain, a minimum mean-square-error （MMSE） combiner is used to refine the estimation results. The simulation results in the frequency band of 5.5 GHz show that the proposed method achieves a good symbol error rate （SER） performance close to the theoretical bound of ideal channel estimation.展开更多
A space-time coded multiple-input multiple-output orthogonal frequency-division multiplexing （MIMO-OFDM） system is considered as a solution to the future wideband wireless communication system. This paper proposes a...A space-time coded multiple-input multiple-output orthogonal frequency-division multiplexing （MIMO-OFDM） system is considered as a solution to the future wideband wireless communication system. This paper proposes an extended Kalman filtering-based （EKF-based） channel estimation method for space-time coded MIMO-OFDM systems. The proposed method can exploit pilot symbols and an extended Kalman filter to estimate channel without any prior knowledge of channel statistics. In comparison with the least square （LS） and the least mean square （LMS） methods, the EKF-based approach has a better performance in theory. Computer simulations demonstrate the proposed method outperforms the LS and LMS methods. Therefore it can offer draznatic system performance improvement at a modest cost of computational complexity.展开更多
A novel pilot-aided ridge regression (RR) channel estimation for SC-FDE system on time-varying frequency selective fading channel is derived. Previous least square (LS) channel estimation, which does not consider and ...A novel pilot-aided ridge regression (RR) channel estimation for SC-FDE system on time-varying frequency selective fading channel is derived. Previous least square (LS) channel estimation, which does not consider and utilize the influence of noise, has poor performance when the observed signal is corrupted abnormally by noise. In order to overcome the inherent disadvantage of LS estimation, the proposed RR estimation uses the influence of noise to get better performance. The performance of this new estimator is examined. The numerical results are presented to show that the new estimation improves the accuracy of estimation especially in low channel signal-to-noise ratio (CSNR) level and outperforms LS estimation. In addition, the proposed RR estimation can get the gains of about 1dB compared with LS estimation.展开更多
A channel estimation approach for orthogonal frequency division multiplexing with multiple-input and multipleoutput （MIMO-OFDM） in rapid fading channels is proposed. This approach combines the advantages of an optim...A channel estimation approach for orthogonal frequency division multiplexing with multiple-input and multipleoutput （MIMO-OFDM） in rapid fading channels is proposed. This approach combines the advantages of an optimal training sequence based least-square （OLS） algorithm and an expectation-maximization （EM） algorithm. The channels at the training blocks are estimated using an estimator based on the OLS algorithm. To compensate for the fast Rayleigh fading at the data blocks, a time domain based Gaussian interpolation filter is presented. Furthermore, an EM algorithm is introduced to improve the performance of channel estimation by a few iterations. Simulations show that this channel estimation approach can effectively track rapid channel variation.展开更多
Higher transmission rate is one of the technological features of promi-nently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing(MIMO–OFDM).One among an effec...Higher transmission rate is one of the technological features of promi-nently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing(MIMO–OFDM).One among an effective solution for channel estimation in wireless communication system,spe-cifically in different environments is Deep Learning(DL)method.This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder(CNNAE)classifier for MIMO-OFDM systems.A CNNAE classi-fier is one among Deep Learning(DL)algorithm,in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another.Improved performances are achieved by using CNNAE based channel estimation,in which extension is done for channel selection as well as achieve enhanced performances numerically,when compared with conventional estimators in quite a lot of scenar-ios.Considering reduction in number of parameters involved and re-usability of weights,CNNAE based channel estimation is quite suitable and properlyfits to the video signal.CNNAE classifier weights updation are done with minimized Sig-nal to Noise Ratio(SNR),Bit Error Rate(BER)and Mean Square Error(MSE).展开更多
In multi-user multiple input multiple output （MU-MIMO） systems, the outdated channel state information at the transmit- ter caused by channel time variation has been shown to greatly reduce the achievable ergodic su...In multi-user multiple input multiple output （MU-MIMO） systems, the outdated channel state information at the transmit- ter caused by channel time variation has been shown to greatly reduce the achievable ergodic sum capacity. A simple yet effec- tive solution to this problem is presented by designing a channel extrapolator relying on Karhunen-Loeve （KL） expansion of time- varying channels. In this scheme, channel estimation is done at the base station （BS） rather than at the user terminal （UT）, which thereby dispenses the channel parameters feedback from the UT to the BS. Moreover, the inherent channel correlation and the parsimonious parameterization properties of the KL expan- sion are respectively exploited to reduce the channel mismatch error and the computational complexity. Simulations show that the presented scheme outperforms conventional schemes in terms of both channel estimation mean square error （MSE） and ergodic capacity.展开更多
A new channel estimation and data detection joint algorithm is proposed for multi-input multi-output （MIMO） - orthogonal frequency division multiplexing （OFDM） system using linear minimum mean square error （LMMSE...A new channel estimation and data detection joint algorithm is proposed for multi-input multi-output （MIMO） - orthogonal frequency division multiplexing （OFDM） system using linear minimum mean square error （LMMSE）- based space-alternating generalized expectation-maximization （SAGE） algorithm. In the proposed algorithm, every sub-frame of the MIMO-OFDM system is divided into some OFDM sub-blocks and the LMMSE-based SAGE algorithm in each sub-block is used. At the head of each sub-flame, we insert training symbols which are used in the initial estimation at the beginning. Channel estimation of the previous sub-block is applied to the initial estimation in the current sub-block by the maximum-likelihood （ML） detection to update channel estimatjon and data detection by iteration until converge. Then all the sub-blocks can be finished in turn. Simulation results show that the proposed algorithm can improve the bit error rate （BER） performance.展开更多
In this paper, an adaptive channel estimation for MIMO OFDM is proposed. A set of pilot tones first are placed in each OFDM block, then the channel frequency response of these pilot tones are adaptively estimated by r...In this paper, an adaptive channel estimation for MIMO OFDM is proposed. A set of pilot tones first are placed in each OFDM block, then the channel frequency response of these pilot tones are adaptively estimated by reeursive least squares （RLS） directly in frequency domain not in time domain. Then after the estimation of the channel frequency response of pilot tones, to obtain the channel frequency response of data tones, a new interpolation method based on DFT different from traditional linear interpolation method according to adjacent pilot tones is proposed. Simulation results show good performance of the technique.展开更多
A new channel estimation method for orthogonal frequency division multiplexing （OFDM） system with large subcarriers and serious intercarrier interference （ICI） is proposed. The channel frequency-domain （ CFD ） m...A new channel estimation method for orthogonal frequency division multiplexing （OFDM） system with large subcarriers and serious intercarrier interference （ICI） is proposed. The channel frequency-domain （ CFD ） matrix of each delay path is factorized to the product of a diagonal delay matrix and a circular ICI matrix in this model. To reduce the coefficient number, the circular ICI ma- trix is squeezed by using Hamming-window as the reshaping pulse in the transmitter. Meanwhile, the elements of the diagonal delay matrix are approximated with a discrete prolate spheroidal basis ex- pansion model （DPS-BEM）. A least-square （LS） estimator is used to estimate the reduced channel coefficients. The proposed method is theoretically derived and simulated. The simulation results in- dicate that the model has good performance and is appropriate for various channel environments. The method also has low complexity and good spectral efficiency.展开更多
The channel estimation technique is investigated in OFDM communication systems with multi-antenna Amplify-and-Forward(AF) relay.The Space-Time Block Code(STBC) is applied at the transmitter of the relay to obtain dive...The channel estimation technique is investigated in OFDM communication systems with multi-antenna Amplify-and-Forward(AF) relay.The Space-Time Block Code(STBC) is applied at the transmitter of the relay to obtain diversity gain.According to the transmission characteristics of OFDM symbols on multiple antennas,a pilot-aided Linear Minimum Mean-Square-Error(LMMSE) channel estimation algorithm with low complexity is designed.Simulation results show that,the proposed LMMSE estimator outperforms least-square estimator and approaches the optimal estimator without error in the performance of Symbol Error Ratio(SER) under several modulation modes,and has a good estimation effect in the realistic relay communication scenario.展开更多
智能反射面(Reconfigurable Intelligent Surface,RIS)有着操纵性强、能耗低、方便部署等优势,已成为6G(第六代移动通信)的关键技术。研究了关于智能反射面的信道估计算法,对于传统算法在传播时路径会因角度原因发生偏移的情况,采用了Tu...智能反射面(Reconfigurable Intelligent Surface,RIS)有着操纵性强、能耗低、方便部署等优势,已成为6G(第六代移动通信)的关键技术。研究了关于智能反射面的信道估计算法,对于传统算法在传播时路径会因角度原因发生偏移的情况,采用了Tucker分解的稀疏角度域高阶奇异值分解(High Order Singular Value Decomposition,HOSVD)信道估计算法来解决路径偏移的问题。为了验证所提出算法的鲁棒性,对比了传统的交替最小二乘法信道估计算法,可以得到不管是在用户数量、传播的路径偏移上都能取得比传统的信道估计算法更好的归一化最小均方误差(Normalized Mean Squared Error,NMSE)效果。展开更多
In this paper, the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analysed through a statistical-mechanical appr...In this paper, the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analysed through a statistical-mechanical approach. Replica analyses focus on analytically studying how the minimum mean square error （MMSE） channel estimation error appears in a multiuser channel capacity formula. And the relevant mathematical expressions are derived. At the same time, numerical simulation results are demonstrated to validate the Replica analyses. The simulation results show how the system parameters, such as channel estimation error, system load and signal-to-noise ratio, affect the channel capacity.展开更多
Several nondestructive assay (NDA) methods to quantify special nuclear materials use calibration curves that are linear in the predictor, either directly or as an intermediate step. The linear response model is also o...Several nondestructive assay (NDA) methods to quantify special nuclear materials use calibration curves that are linear in the predictor, either directly or as an intermediate step. The linear response model is also often used to illustrate the fundamentals of calibration, and is the usual detector behavior assumed when evaluating detection limits. It is therefore important for the NDA community to have a common understanding of how to implement a linear calibration according to the common method of least squares and how to assess uncertainty in inferred nuclear quantities during the prediction stage following calibration. Therefore, this paper illustrates regression, residual diagnostics, effect of estimation errors in estimated variances used for weighted least squares, and variance propagation in a form suitable for implementation. Before the calibration can be used, a transformation of axes is required;this step, along with variance propagation is not currently explained in available NDA standard guidelines. The role of systematic and random uncertainty is illustrated and expands on that given previously for the chosen practical NDA example. A listing of open-source software is provided in the Appendix.展开更多
The technique of SNR estimation is one of the key technologies in adaptive frequency hopping system. The methods of channel quality estimation for non-linear continuous phase modulation (CPM) signals have some limitat...The technique of SNR estimation is one of the key technologies in adaptive frequency hopping system. The methods of channel quality estimation for non-linear continuous phase modulation (CPM) signals have some limitations. Therefore, the algorithm of channel quality estimation for CPM signals is worthy of further study. Some similar phase characteristics between sampling CPM and MPSK motivate us to propose a channel estimation algorithm with applications to nonlinear CPM using linear modulation signal processing. A comprehensive analysis of LDPC-CPM schemes using proposed algorithm is presented, and simulation results indicate that the proposed method can not only estimate channel quality well but also make the normalized MSE (NMSE) of SNR estimate close to/less than 0.1 dB at SNR of 4 dB using short block codes. It shows that the algorithm in this paper is effective enough to estimate the signal to noise ratio (SNR). Meanwhile, the algorithm in this paper reduces the complexity of computation compared with other traditional algorithms.展开更多
基金The National Hi-Tech Development Plan (863-317-03-01-02-04-20).
文摘Based on the fact that the variation of tile direction of arrival (DOA) isslower than that of the channel fading, the steering vector of the desired signal is estimatedfirstly using a subspace decomposition method and then a constrained condition is configured.Traffic signals are further employed to estimate the channel vector based on the constrained leastsquares criterion. We use the iterative least squares with projection (ILSP) algorithm initializedby the pilot to get the estimation. The accuracy of channel estimation and symbol detection can beprogressively increased through the iteration procedure of the ILSP algorithm. Simulation resultsdemonstrate that the proposed algorithm improves the system performance effectively compared withthe conventional 2-D RAKE receiver.
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.
基金The Open Research Fund of National Mobile Communications Research Laboratory of Southeast University(No.2013D02)the Fundamental Research Funds for the Central Universities(No.30920130122004)the National Natural Science Foundation of China(No.61271230,61472190)
文摘A pilot pattern across two orthogonal frequency division multiplexing OFDM symbols with a special structure is designed for the channel estimation of OFDM systems with inphase and quadrature IQ imbalances at the receiver.A high-efficiency time-domain TD least square LS channel estimator and a low-complexity frequency-domain Gaussian elimination GE equalizer are proposed to eliminate IQ distortion.The former estimator can significantly suppress channel noise by a factor N/L＋1 over the existing frequency-domain FD LS where N and L＋1 are the total number of subcarriers and the length of cyclic prefix and the proposed GE requires only 2N complex multiplications per OFDM symbol.Simulation results show that by exploiting the TD property of the channel the proposed TD-LS channel estimator obtains a significant signal-to-noise ratio gain over the existing FD-LS one whereas the proposed low-complexity GE compensation achieves the same bit error rate BER performance as the existing LS one.
文摘Under analyzing several characteristics of frequency-selective fast fading channels, such as large Doppler spread and multi-path interference, a low-dimensional Kalman filter method based on pilot signals is presented for the channel estimation of orthogonal frequency division multiplexing （OFDM） systems. For simplicity, a one-dimensional autoregressive （AR） process is used to model the time-varying channel, and the least square （LS） algorithm based on pilot signals is adopted to track the time-varying channel fading factor a. The low-dimensional Kalman filter estimator greatly reduces the complexity of the high-dimensional Kalman filter. To utilize the relationship of fading channel in frequency domain, a minimum mean-square-error （MMSE） combiner is used to refine the estimation results. The simulation results in the frequency band of 5.5 GHz show that the proposed method achieves a good symbol error rate （SER） performance close to the theoretical bound of ideal channel estimation.
基金Project supported by the National Natural Science Foundation of China （Grant No.60572157）, and the National High- Technology Research and Development Program of China （Grant No.2003AA123310）
文摘A space-time coded multiple-input multiple-output orthogonal frequency-division multiplexing （MIMO-OFDM） system is considered as a solution to the future wideband wireless communication system. This paper proposes an extended Kalman filtering-based （EKF-based） channel estimation method for space-time coded MIMO-OFDM systems. The proposed method can exploit pilot symbols and an extended Kalman filter to estimate channel without any prior knowledge of channel statistics. In comparison with the least square （LS） and the least mean square （LMS） methods, the EKF-based approach has a better performance in theory. Computer simulations demonstrate the proposed method outperforms the LS and LMS methods. Therefore it can offer draznatic system performance improvement at a modest cost of computational complexity.
基金Sponsored by the National Natural Science Foundation of China & Civil Aviation Administration of China(Grant No.61071104)the Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory(Grant No.ITD-U10006)
文摘A novel pilot-aided ridge regression (RR) channel estimation for SC-FDE system on time-varying frequency selective fading channel is derived. Previous least square (LS) channel estimation, which does not consider and utilize the influence of noise, has poor performance when the observed signal is corrupted abnormally by noise. In order to overcome the inherent disadvantage of LS estimation, the proposed RR estimation uses the influence of noise to get better performance. The performance of this new estimator is examined. The numerical results are presented to show that the new estimation improves the accuracy of estimation especially in low channel signal-to-noise ratio (CSNR) level and outperforms LS estimation. In addition, the proposed RR estimation can get the gains of about 1dB compared with LS estimation.
基金Project supported by the National High-Technology Research and Development Program of China （Grant No. 2003AA123- 31007）, and the National Natural Science Foundation of China （Grant No.60272079）
文摘A channel estimation approach for orthogonal frequency division multiplexing with multiple-input and multipleoutput （MIMO-OFDM） in rapid fading channels is proposed. This approach combines the advantages of an optimal training sequence based least-square （OLS） algorithm and an expectation-maximization （EM） algorithm. The channels at the training blocks are estimated using an estimator based on the OLS algorithm. To compensate for the fast Rayleigh fading at the data blocks, a time domain based Gaussian interpolation filter is presented. Furthermore, an EM algorithm is introduced to improve the performance of channel estimation by a few iterations. Simulations show that this channel estimation approach can effectively track rapid channel variation.
文摘Higher transmission rate is one of the technological features of promi-nently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing(MIMO–OFDM).One among an effective solution for channel estimation in wireless communication system,spe-cifically in different environments is Deep Learning(DL)method.This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder(CNNAE)classifier for MIMO-OFDM systems.A CNNAE classi-fier is one among Deep Learning(DL)algorithm,in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another.Improved performances are achieved by using CNNAE based channel estimation,in which extension is done for channel selection as well as achieve enhanced performances numerically,when compared with conventional estimators in quite a lot of scenar-ios.Considering reduction in number of parameters involved and re-usability of weights,CNNAE based channel estimation is quite suitable and properlyfits to the video signal.CNNAE classifier weights updation are done with minimized Sig-nal to Noise Ratio(SNR),Bit Error Rate(BER)and Mean Square Error(MSE).
基金supported by the National Natural Science Foundation of China (6096200161071088)+2 种基金the Natural Science Foundation of Fujian Province of China (2012J05119)the Fundamental Research Funds for the Central Universities (11QZR02)the Research Fund of Guangxi Key Lab of Wireless Wideband Communication & Signal Processing (21104)
文摘In multi-user multiple input multiple output （MU-MIMO） systems, the outdated channel state information at the transmit- ter caused by channel time variation has been shown to greatly reduce the achievable ergodic sum capacity. A simple yet effec- tive solution to this problem is presented by designing a channel extrapolator relying on Karhunen-Loeve （KL） expansion of time- varying channels. In this scheme, channel estimation is done at the base station （BS） rather than at the user terminal （UT）, which thereby dispenses the channel parameters feedback from the UT to the BS. Moreover, the inherent channel correlation and the parsimonious parameterization properties of the KL expan- sion are respectively exploited to reduce the channel mismatch error and the computational complexity. Simulations show that the presented scheme outperforms conventional schemes in terms of both channel estimation mean square error （MSE） and ergodic capacity.
基金Supported by the National Natural Science Foundation of China （No. 61001105）, the National Science and Technology Major Projects （No. 2011ZX03001- 007- 03） and Beijing Natural Science Foundation （No. 4102043）.
文摘A new channel estimation and data detection joint algorithm is proposed for multi-input multi-output （MIMO） - orthogonal frequency division multiplexing （OFDM） system using linear minimum mean square error （LMMSE）- based space-alternating generalized expectation-maximization （SAGE） algorithm. In the proposed algorithm, every sub-frame of the MIMO-OFDM system is divided into some OFDM sub-blocks and the LMMSE-based SAGE algorithm in each sub-block is used. At the head of each sub-flame, we insert training symbols which are used in the initial estimation at the beginning. Channel estimation of the previous sub-block is applied to the initial estimation in the current sub-block by the maximum-likelihood （ML） detection to update channel estimatjon and data detection by iteration until converge. Then all the sub-blocks can be finished in turn. Simulation results show that the proposed algorithm can improve the bit error rate （BER） performance.
基金the National Nature Science Foundation ofChina under Grant No. 60372107.
文摘In this paper, an adaptive channel estimation for MIMO OFDM is proposed. A set of pilot tones first are placed in each OFDM block, then the channel frequency response of these pilot tones are adaptively estimated by reeursive least squares （RLS） directly in frequency domain not in time domain. Then after the estimation of the channel frequency response of pilot tones, to obtain the channel frequency response of data tones, a new interpolation method based on DFT different from traditional linear interpolation method according to adjacent pilot tones is proposed. Simulation results show good performance of the technique.
基金Supported by the National Natural Science Foundation of China(61101131)
文摘A new channel estimation method for orthogonal frequency division multiplexing （OFDM） system with large subcarriers and serious intercarrier interference （ICI） is proposed. The channel frequency-domain （ CFD ） matrix of each delay path is factorized to the product of a diagonal delay matrix and a circular ICI matrix in this model. To reduce the coefficient number, the circular ICI ma- trix is squeezed by using Hamming-window as the reshaping pulse in the transmitter. Meanwhile, the elements of the diagonal delay matrix are approximated with a discrete prolate spheroidal basis ex- pansion model （DPS-BEM）. A least-square （LS） estimator is used to estimate the reduced channel coefficients. The proposed method is theoretically derived and simulated. The simulation results in- dicate that the model has good performance and is appropriate for various channel environments. The method also has low complexity and good spectral efficiency.
基金Supported by the National Natural Science Foundation of Jiangsu province(No.08KJB510015)
文摘The channel estimation technique is investigated in OFDM communication systems with multi-antenna Amplify-and-Forward(AF) relay.The Space-Time Block Code(STBC) is applied at the transmitter of the relay to obtain diversity gain.According to the transmission characteristics of OFDM symbols on multiple antennas,a pilot-aided Linear Minimum Mean-Square-Error(LMMSE) channel estimation algorithm with low complexity is designed.Simulation results show that,the proposed LMMSE estimator outperforms least-square estimator and approaches the optimal estimator without error in the performance of Symbol Error Ratio(SER) under several modulation modes,and has a good estimation effect in the realistic relay communication scenario.
文摘智能反射面(Reconfigurable Intelligent Surface,RIS)有着操纵性强、能耗低、方便部署等优势,已成为6G(第六代移动通信)的关键技术。研究了关于智能反射面的信道估计算法,对于传统算法在传播时路径会因角度原因发生偏移的情况,采用了Tucker分解的稀疏角度域高阶奇异值分解(High Order Singular Value Decomposition,HOSVD)信道估计算法来解决路径偏移的问题。为了验证所提出算法的鲁棒性,对比了传统的交替最小二乘法信道估计算法,可以得到不管是在用户数量、传播的路径偏移上都能取得比传统的信道估计算法更好的归一化最小均方误差(Normalized Mean Squared Error,NMSE)效果。
基金Project supported by the National Nature Science Foundation of China (Grant Nos 60773085 and 60801051)
文摘In this paper, the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analysed through a statistical-mechanical approach. Replica analyses focus on analytically studying how the minimum mean square error （MMSE） channel estimation error appears in a multiuser channel capacity formula. And the relevant mathematical expressions are derived. At the same time, numerical simulation results are demonstrated to validate the Replica analyses. The simulation results show how the system parameters, such as channel estimation error, system load and signal-to-noise ratio, affect the channel capacity.
文摘Several nondestructive assay (NDA) methods to quantify special nuclear materials use calibration curves that are linear in the predictor, either directly or as an intermediate step. The linear response model is also often used to illustrate the fundamentals of calibration, and is the usual detector behavior assumed when evaluating detection limits. It is therefore important for the NDA community to have a common understanding of how to implement a linear calibration according to the common method of least squares and how to assess uncertainty in inferred nuclear quantities during the prediction stage following calibration. Therefore, this paper illustrates regression, residual diagnostics, effect of estimation errors in estimated variances used for weighted least squares, and variance propagation in a form suitable for implementation. Before the calibration can be used, a transformation of axes is required;this step, along with variance propagation is not currently explained in available NDA standard guidelines. The role of systematic and random uncertainty is illustrated and expands on that given previously for the chosen practical NDA example. A listing of open-source software is provided in the Appendix.
文摘The technique of SNR estimation is one of the key technologies in adaptive frequency hopping system. The methods of channel quality estimation for non-linear continuous phase modulation (CPM) signals have some limitations. Therefore, the algorithm of channel quality estimation for CPM signals is worthy of further study. Some similar phase characteristics between sampling CPM and MPSK motivate us to propose a channel estimation algorithm with applications to nonlinear CPM using linear modulation signal processing. A comprehensive analysis of LDPC-CPM schemes using proposed algorithm is presented, and simulation results indicate that the proposed method can not only estimate channel quality well but also make the normalized MSE (NMSE) of SNR estimate close to/less than 0.1 dB at SNR of 4 dB using short block codes. It shows that the algorithm in this paper is effective enough to estimate the signal to noise ratio (SNR). Meanwhile, the algorithm in this paper reduces the complexity of computation compared with other traditional algorithms.
