Mixture Kalman Filtering for Joint Carrier Recovery and Channel Estimation in Time-selective Rayleigh Fading Channels
This paper proposes a new blind algorithm, based on Mixture Kalman Filtering (MKF), for joint carrier recovery and channel estimation in time-selective Rayleigh fading channels. MKF is a powerful tool for estimating unknown parameters in non-linear, non-Gaussian, real-time applications. We use a combination of Kalman filtering and Sequential Monte Carlo Sampling to estimate the channel fading coefficients and joint posterior probability density of the unknown carrier offset and transmitted data...[Show more]
|Collections||ANU Research Publications|
|Source:||On the Construction of Low-pass Filters on the Unit Sphere|
|01_Nasir_Mixture_Kalman_Filtering_for_2011.pdf||136.99 kB||Adobe PDF||Request a copy|
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