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- W2129094593 abstract "The paper addresses the problem of joint velocity estimation and data detection in a realistic scenario where mobile velocity changes continuously, resulting in non-stationary fast fading channels. A time-varying AR model and a Gauss-Markov model are used to describe the respective fading channel and variation of velocity. A connection is shown between the coefficients of the TVAR model and mobile velocity which makes the joint estimation and detection possible. A hierarchical dynamic state space model is formed for the problem, and a particle filtering algorithm is proposed. In particular, a hybrid importance function and the mixture Kalman filter are used to achieve efficient implementation of particle filtering. Simulation results are provided that show the performance of the particle filtering algorithm." @default.
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- W2129094593 date "2004-03-22" @default.
- W2129094593 modified "2023-09-23" @default.
- W2129094593 title "Joint velocity estimation and symbol detection in non-stationary fading channels by particle filtering" @default.
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- W2129094593 doi "https://doi.org/10.1109/glocom.2003.1258639" @default.
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