Blind equalization without gain identification

S. Verdu, Brian Anderson, Rodney Kennedy

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

Blind equalization up to a constant gain of linear timeinvariant channels is studied. Dropping the requirement of gain identification allows equalizer anchoring. This results in the elimination of
a degree of freedom that causes ill-convergence of conventional blind equalizers, ahd affords the possibility of using simple update rules based on the stochastic approximation of output energy. Unlike conventional blind equalizers, truncations of the nonrecursive infinite-dimensional realizations of those equalizers inherit the convergence properties of their infinitely parametrized counterparts. A globally convergent blind recursive equalizer for channels without all-pass sections is obtained based on the exact equalization of the minimum-phase part of the channel and the identification of its nonminimum-phase zeros.
Original languageEnglish
Pages (from-to)292–297
JournalIEEE Transactions on Information Theory
Volume31
Issue number9
Publication statusPublished - Jan 1993

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