Joint Data and Kalman Estimation for Rayleigh Fading Channels
Wireless Personal Communications: An International Journal
A new class of particle filters for random dynamic systems with unknown statistics
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Applied Signal Processing
Game theory approach to discrete H∞ filter design
IEEE Transactions on Signal Processing
Nonlinear Channel Equalization With Gaussian Processes for Regression
IEEE Transactions on Signal Processing - Part II
Robust extended Kalman filtering
IEEE Transactions on Signal Processing
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We propose cost reference particle filter (CRPF) and extended game theory-based H∞ filter approaches to the problem of estimating frequency-selective and slowly varying nonlinear channels with unknown noise statistics. The proposed approaches have a common advantageous feature that the noise information is not required in their applications. The simulation results justify that both approaches are effective, and that CRPF is more robust against highly nonlinear and drastically varying channels.