Blind equalization using least-squares lattice prediction

Second-order statistics of the received signal can be used to equalize a co mmunication channel without knowledge of the transmitted sequence. Blind ze ro-forcing (ZF) and minimum mean-square error (MMSE) equalization can be ac hieved with linear prediction-error filtering. The equivalence with the equ alizers derived by Giannakis and Halford is shown, and adaptive predictors that result in a lattice filtering structure are applied. The required chan nel coefficient vector is obtained with adaptive eigen-pair tracking. Eithe r forward or backward prediction errors can be used. The performance of the blind equalizer is examined by simulations. The MMSE of the optimum FSE is approached, and the algorithm exhibits robustness to channels with common subchannel zeros.