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
In this paper, the asymptotic sum rate of a multi-user distributed antenna system （DAS） is analyzed. To mitigate inter-user interference, minimum mean squared error （MMSE） receivers are utilized to cooperatively p...In this paper, the asymptotic sum rate of a multi-user distributed antenna system （DAS） is analyzed. To mitigate inter-user interference, minimum mean squared error （MMSE） receivers are utilized to cooperatively process received signals in the uplink. It shows that inter-user interference is efficiently mitigated and the uplink sum rate of a multi-user DAS is greatly improved by adopting MMSE receivers. For very large number of users and remote antennas, the asymptotic uplink sum rate of MMSE receivers is derived by using virtue of the random matrix theory, which can be The approximation is verified to be quite accurate by Monte Carlo simply calculated in an iterative way simulations.展开更多
The distributed antenna system （DAS） is considered as a promising architecture for future wireless access. This paper describes the uplink of a power-controlled circular-layout DAS （CL-DAS） with minimum mean-squar...The distributed antenna system （DAS） is considered as a promising architecture for future wireless access. This paper describes the uplink of a power-controlled circular-layout DAS （CL-DAS） with minimum mean-square error （MMSE） receivers. Results from random matrix theory are used to show that for such a DAS, the per-user sum rate and the total transmit power both converge as the number of users and antennas goes to infinity with a constant ratio of antennas to users. The relationship between the asymptotic per-user sum rate and the asymptotic total transmit power is given for all possible values of the radius of the circle on which antennas are placed. This rate-power relationship is then used to find the optimal radius. With this optimal radius, the CL-DAS is proved to offer a significant gain compared with a traditional co-located antenna system. Simulation results demonstrate the validity of the analysis and the superiority of the DAS.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.
文摘In this paper, the asymptotic sum rate of a multi-user distributed antenna system （DAS） is analyzed. To mitigate inter-user interference, minimum mean squared error （MMSE） receivers are utilized to cooperatively process received signals in the uplink. It shows that inter-user interference is efficiently mitigated and the uplink sum rate of a multi-user DAS is greatly improved by adopting MMSE receivers. For very large number of users and remote antennas, the asymptotic uplink sum rate of MMSE receivers is derived by using virtue of the random matrix theory, which can be The approximation is verified to be quite accurate by Monte Carlo simply calculated in an iterative way simulations.
基金Supported by the National Natural Science Foundation of China (No. 90204001)
文摘The distributed antenna system （DAS） is considered as a promising architecture for future wireless access. This paper describes the uplink of a power-controlled circular-layout DAS （CL-DAS） with minimum mean-square error （MMSE） receivers. Results from random matrix theory are used to show that for such a DAS, the per-user sum rate and the total transmit power both converge as the number of users and antennas goes to infinity with a constant ratio of antennas to users. The relationship between the asymptotic per-user sum rate and the asymptotic total transmit power is given for all possible values of the radius of the circle on which antennas are placed. This rate-power relationship is then used to find the optimal radius. With this optimal radius, the CL-DAS is proved to offer a significant gain compared with a traditional co-located antenna system. Simulation results demonstrate the validity of the analysis and the superiority of the DAS.
