Title :
A blind particle filtering detector for joint channel estimation, tracking and data detection over flat fading channels
Author :
Yufei Huang ; Djuric, Petar M.
Author_Institution :
Dept. of Electr. & Comput. Eng., State Univ. of New York at Stony Brook, Stony Brook, NY, USA
Abstract :
A new particle filtering detector is proposed for joint estimation of channel model coefficients, channel tracking, and signal detection over flat Rayleigh fading channels. The detector employs a hybrid importance function and a mixture Kalman filter which result in a highly efficient implementation. In addition, by considering the practical limitation of the system and physical interpretation of the adopted AR(2) channel model, we realize a fully blind particle filtering implementation. Simulation are provided to show the performance of the proposed detector.
Keywords :
Kalman filters; Rayleigh channels; autoregressive processes; channel estimation; particle filtering (numerical methods); signal detection; adopted AR channel model; blind particle filtering detector; channel model coefficient estimation; data detection; fiat Rayleigh fading channel tracking; hybrid importance function; mixture Kalman filter; signal detection; Abstracts; Channel estimation; Detectors; Fading; Filtering; Gold; Joints;
Conference_Titel :
Signal Processing Conference, 2002 11th European
Conference_Location :
Toulouse
