Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering
© Huang et al. 2005
Received: 30 April 2004
Published: 28 April 2005
We propose a method for blind multiuser detection (MUD) in synchronous systems over flat and fast Rayleigh fading channels. We adopt an autoregressive-moving-average (ARMA) process to model the temporal correlation of the channels. Based on the ARMA process, we propose a novel time-observation state-space model (TOSSM) that describes the dynamics of the addressed multiuser system. The TOSSM allows an MUD with natural blending of low-complexity particle filtering (PF) and mixture Kalman filtering (for channel estimation). We further propose to use a more efficient PF algorithm known as the stochastic -algorithm (SMA), which, although having lower complexity than the generic PF implementation, maintains comparable performance.
Keywordsmultiuser detection time-observation state-space model fading channel estimation particle filtering mixture Kalman filter
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