Extended Kalman filtering-based channel estimation for space-time coded MIMO-OFDM systems

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.

SURGE FORECAST FOR AERONAUTICAL ENGINES WITH EXTENDED KALMAN ESTIMATION

Abstract In this paper,the theory of extended Kalman estimation is applied to state estimate ofcompression system, for which a nonlinear model is developed by Greitzer.A criterion ofdetermining whether surge will occur in a turbine engine is presented.The combination ofstate estimation and the criterion of determining surge forms a surge prediction algorithm,which is the theoretical basis of designing a surge indicator for the turbine engine.

Joint Channel Estimation and Decoding Design for 5G-Enabled V2V Channel

This paper addresses the problem of channel estimation in 5G-enabled vehicular-to-vehicular(V2V) channels with high-mobility environments and non-stationary feature. Considering orthogonal frequency division multiplexing(OFDM) system, we perform extended Kalman filter(EKF) for channel estimation in conjunction with Iterative Detector & Decoder(IDD) at the receiver to improve the estimation accuracy. The EKF is proposed for jointly estimating the channel frequency response and the time-varying time correlation coefficients. And the IDD structure is adopted to reduce the estimation errors in EKF. The simulation results show that, compared with traditional methods, the proposed method effectively promotes the system performance.

Identification of flexible buildings with bending deformation and the unmeasured earthquake ground motion

It is important to explore efficient algorithms for the identification of both structural parameters and unmeasured earthquake ground motion.Recently,the authors proposed an algorithm for the identification of shear-type buildings and unknown earthquake excitation.In this paper,it is extended to the investigation of the identification of flexible buildings with bending deformation and the unmeasured earthquake ground motion.In the absolute co-ordinate system,the unmeasured ground motion can be treated as an unknown translational force and a bending moment at the 1st floor level of a flexible building.Structural unknown parameters above the 1st story of the building can be identified by the extended Kalman estimator and the 1st story stiffness and the unmeasured ground motion are subsequently estimated based on the least-squares estimation.The proposed algorithm is further extended to the identification of tall bending-type buildings based on substructure approach.Inter-connection effect between sub-buildings is treated as‘additional unknown inputs’to sub-buildings,which are estimated by the extended Kalman estimator without the measurements of rotational responses.Numerical examples demonstrate the identification of a multi-story,tall bending-type building and its unmeasured earthquake ground motions using only partial measurements of structural absolute responses.