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.
This article is part of the series Advanced Signal Processing Algorithms for Wireless Communications.
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.2005.130
The electronic version of this article is the complete one and can be found online at: http://jwcn.eurasipjournals.com/content/2005/2/960165
|Received:||30 April 2004|
|Revisions received:||16 September 2004|
|Published:||28 April 2005|
© 2005 Huang et al.
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