Projection minimization algorithm for blind channel equalizer
Signal Processing
Fast adaptive blind MMSE equalizer for multichannel FIR systems
EURASIP Journal on Applied Signal Processing
On MMSE methods for blind identification of OFDM-based SIMO systems
WOCN'09 Proceedings of the Sixth international conference on Wireless and Optical Communications Networks
On the performance improvements of max-SINR equalizers in wireless communications
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
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A family of new MMSE blind channel equalization algorithms based on second-order statistics are proposed. Instead of estimating the channel impulse response, we directly estimate the cross-correlation function needed in Wiener-Hopf filters. We develop several different schemes to estimate the cross-correlation vector, with which different Wiener filters are derived according to minimum mean square error (MMSE). Unlike many known sub-space methods, these equalization algorithms do not rely on signal and noise subspace separation and are consequently more robust to channel order estimation errors. Their implementation requires no adjustment for either single- or multiple-user systems. They can effectively equalize single-input multiple-output (SIMO) systems and can reduce the multiple-input multiple-output (MIMO) systems into a memoryless signal mixing system for source separation. The implementations of these algorithms on SIMO system are given, and simulation examples are provided to demonstrate their superior performance over some existing algorithms