ONLINE BLIND MULTICHANNEL EQUALIZATION BASED ON MUTUALLY REFERENCED FILTERS

This paper presents a novel approach to the blind linear equalization of possibly nonminimum phase and time-varying communication channels, In the context of channel diversity, we introduce the concept of mutua lly referenced equalizers (MRE's) in which several filters are conside red, the outputs of which act as training signals for each other, A co rresponding (constrained) multidimensional mean-square error (MSE) cos t function is derived, the minimization of which is shown to be a nece ssary and sufficient condition for equalization, The links with a stan dard linear prediction problem are demonstrated, The proposed techniqu e exhibits properties of important practical concern: 1) The proposed algorithm is globally convergent. 2) Simple closed-form solutions exis t for the MRE's, but the MRE's also lend themselves readily to adaptiv e implementation, In particular, the recursive least-squares (RLS) alg orithm can be used to offer optimal convergence rate. 3) The MRE metho d provides a solution for all equalization delays, which results in ro bustness properties with respect to SNR and ill-defined channel length s.