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

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Abstract

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.

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Correspondence to Yufei Huang.

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Huang, Y., Zhang, J.(., Luna, I.T. et al. Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering. J Wireless Com Network 2005, 960165 (2005). https://doi.org/10.1155/WCN.2005.130

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Keywords

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