Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering
1 Department of Electrical Engineering, The University of Texas at San Antonio, San Antonio, TX 78249-06615, USA
2 Department of Electrical and Computer Engineering, University of New Hampshire, Durham, NH 03824, USA
3 Departamento de Física Aplicada, Universidad de Granada, Granada 18071, Spain
4 Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY 11794-2350, USA
EURASIP Journal on Wireless Communications and Networking 2005, 2005:960165 doi:10.1155/WCN.2005.130Published: 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.