Column-anchored zeroforcing blind equalization for multiuser wireless FIR channels

We propose a direct blind zeroforcing approach to cancel intersymbol interf erence (ISI) in multiple user finite impulse response (FIR) channels, By se lectively anchoring columns of the channel convolution matrix, we present t wo column-anchored zeroforcing equalizers (CAZE), one without output delay and one with a chosen delay. Unlike many known blind identification algorit hms, these equalizers do not need an accurate estimate of the channel order s. Exploiting second-order statistics (SOS) of the received signals, they c an retain preselected d columns in the channel convolution matrix (d is the number of users) and force the remaining columns to zero. GAZE can effecti vely equalize single-input-multiple-output (SIMO) systems and can reduce dy namic multiple-input-multiple-output (MIMO) systems into a memoryless signa l mixing system for source separation. Simulation results show that the GAZ E is not only effective for blind equalization of linear quadrature amplitu de modulation (QAM) systems, but it is also applicable to the nonlinear GMS K modulation in the popular wireless GSM systems when computational cost se verely limits the use of nonlinear methods such as the Viterbi algorithm.