Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Mixture Filtering Approaches to Blind Equalization Based on Estimation of Time-Varying and Multi-Path Channels

  • Lim, Jaechan (Department of Electronic Engineering, Sogang University)
  • Received : 2012.11.04
  • Accepted : 2015.09.11
  • Published : 2016.02.28
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Abstract

In this paper, we propose a number of blind equalization approaches for time-varying andmulti-path channels. The approaches employ cost reference particle filter (CRPF) as the symbol estimator, and additionally employ either least mean squares algorithm, recursive least squares algorithm, or $H{\infty}$ filter (HF) as a channel estimator such that they are jointly employed for the strategy of "Rao-Blackwellization," or equally called "mixture filtering." The novel feature of the proposed approaches is that the blind equalization is performed based on direct channel estimation with unknown noise statistics of the received signals and channel state system while the channel is not directly estimated in the conventional method, and the noise information if known in similar Kalman mixture filtering approach. Simulation results show that the proposed approaches estimate the transmitted symbols and time-varying channel very effectively, and outperform the previously proposed approach which requires the noise information in its application.

Keywords

Acknowledgement

Supported by : National Research Foundation of Korea

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