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Open Access Open Badges Research Article

Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering

Yufei Huang1*, Jianqiu (Michelle) Zhang2, Isabel Tienda Luna3, Petar M Djurić4 and Diego Pablo Ruiz Padillo3

Author Affiliations

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

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EURASIP Journal on Wireless Communications and Networking 2005, 2005:960165  doi:10.1155/WCN.2005.130

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.

multiuser detection; time-observation state-space model; fading channel estimation; particle filtering; mixture Kalman filter