Blind equalization using least-squares lattice prediction

Second-order statistics of the received signal can be used to equalize a communication channel without knowledge of the transmitted sequence. Blind zero-forcing (ZF) and minimum mean-square error (MMSE) equalization can be achieved with linear prediction error filtering. The equivalence with the equalizers derived by Giannakis and Halford (see ibid., vol.45, p.2277-92, 1997) is shown, and adaptive predictors that result in a lattice filtering structure are applied. The required channel coefficient vector is obtained with adaptive eigen-pair tracking. Either 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.