Efficient POCS algorithms for deterministic blind equalization of time-varying channels

We present two POCS (projections onto convex sets) algorithms for deterministic blind equalization of linear time-varying (LTV) channels. Our approach is based on a multichannel LTI representation of LTV channels. We prove a theorem on unique reconstruction/equalization, formulate a POCS algorithm for the resolution of a matrix ambiguity, and show how to cope with unequal subchannel lengths. We also present an alternative POCS algorithm for equalization that avoids a singular value decomposition. Both algorithms are guaranteed to converge to the desired solution.