An enhanced extended Kalman filtering （E2KF） algorithm is proposed in this paper to cope with the joint multiple carrier frequency offsets （CFOs） and time-variant channel estimate for MIMO-OFDM systems over high m...An enhanced extended Kalman filtering （E2KF） algorithm is proposed in this paper to cope with the joint multiple carrier frequency offsets （CFOs） and time-variant channel estimate for MIMO-OFDM systems over high mobility scenarios. It is unveiled that, the auto-regressive （AR） model not only provides an effective method to capture the dynamics of the channel parameters, which enables the prediction capability in the EKF algorithm, but also suggests an method to incorporate multiple successive pilot symbols for the improved measurement update.展开更多
This paper discusses the blind carrier frequency offset （CFO） estimation for orthogonal frequency division multiplexing （OFDM） systems by utilizing trilinear decomposition and genera- lized preceding. Firstly, the...This paper discusses the blind carrier frequency offset （CFO） estimation for orthogonal frequency division multiplexing （OFDM） systems by utilizing trilinear decomposition and genera- lized preceding. Firstly, the generalized precoding is employed to obtain multiple covariance matrices which are requisite for the trilinear model, and then a novel CFO estimation algorithm is proposed for the OFDM system. Compared with both the joint diagonalizer and estimation of signal parameters via rotational invariant technique （ESPRIT）, the proposed algorithm enjoys a better CFO estimation performance. Furthermore, the proposed algorithm can work well without virtual carriers. Simulation results illustrate the performance of this algorithm,展开更多
文摘An enhanced extended Kalman filtering （E2KF） algorithm is proposed in this paper to cope with the joint multiple carrier frequency offsets （CFOs） and time-variant channel estimate for MIMO-OFDM systems over high mobility scenarios. It is unveiled that, the auto-regressive （AR） model not only provides an effective method to capture the dynamics of the channel parameters, which enables the prediction capability in the EKF algorithm, but also suggests an method to incorporate multiple successive pilot symbols for the improved measurement update.
基金supported by the National Natural Science Foundation of China (60801052)the Aeronautical Science Foundation of China(2009ZC52036)+1 种基金Nanjing University of Aeronautics and Astronautics Research Funding (NS2012010 NP2011036)
文摘This paper discusses the blind carrier frequency offset （CFO） estimation for orthogonal frequency division multiplexing （OFDM） systems by utilizing trilinear decomposition and genera- lized preceding. Firstly, the generalized precoding is employed to obtain multiple covariance matrices which are requisite for the trilinear model, and then a novel CFO estimation algorithm is proposed for the OFDM system. Compared with both the joint diagonalizer and estimation of signal parameters via rotational invariant technique （ESPRIT）, the proposed algorithm enjoys a better CFO estimation performance. Furthermore, the proposed algorithm can work well without virtual carriers. Simulation results illustrate the performance of this algorithm,
