Open AccessBlind MMSE Equalization of FIR/IIR Channels Using Oversampling and Multichannel Linear Prediction
Author(s) -
Chen Fangjiong,
Kwong Sam,
Kok ChiWah
Publication year - 2009
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.09.0108.0147
Subject(s) - oversampling , infinite impulse response , finite impulse response , equalization (audio) , control theory (sociology) , channel (broadcasting) , linear prediction , algorithm , blind equalization , minimum mean square error , impulse (physics) , impulse response , mathematics , filter (signal processing) , computer science , digital filter , statistics , telecommunications , artificial intelligence , mathematical analysis , physics , control (management) , bandwidth (computing) , quantum mechanics , estimator , computer vision , decoding methods
A linear‐prediction‐based blind equalization algorithm for single‐input single‐output (SISO) finite impulse response/infinite impulse response (FIR/IIR) channels is proposed. The new algorithm is based on second‐order statistics, and it does not require channel order estimation. By oversampling the channel output, the SISO channel model is converted to a special single‐input multiple‐output (SIMO) model. Two forward linear predictors with consecutive prediction delays are applied to the subchannel outputs of the SIMO model. It is demonstrated that the partial parameters of the SIMO model can be estimated from the difference between the prediction errors when the length of the predictors is sufficiently large. The sufficient filter length for achieving the optimal prediction is also derived. Based on the estimated parameters, both batch and adaptive minimum‐mean‐square‐error equalizers are developed. The performance of the proposed equalizers is evaluated by computer simulations and compared with existing algorithms.