Local convergence of the Sato blind equalizer and generalizationsunder practical constraints
Ding, Z.
Kennedy, R.A.
Anderson, B.D.O.
Johnson, C.R., Jr.
Dept. of Electr. Eng., Auburn Univ., AL;
This paper appears in: Information Theory, IEEE Transactions on
Publication Date: Jan 1993
Volume: 39,
Issue: 1
On page(s): 129-144
ISSN: 0018-9448
References Cited: 22
CODEN: IETTAW
INSPEC Accession Number: 4389176
Digital Object Identifier: 10.1109/18.179350
Current Version Published: 2002-08-06
Abstract
An early use of recursive identification in blind adaptive channel
equalization is an algorithm developed by Y. Sato (1975). An important
generalization of the Sato algorithm with extensive analysis appears in
the work of A. Benveniste et al. (1980). These generalized algorithms
have been shown to possess a desirable global convergence property under
two idealized conditions. The convergence properties of this class of
blind algorithms under practical constraints common to a variety of
channel equalization applications that violate these idealized
conditions are studied. Results show that, in practice, when the
equalizer is finite-dimensional and/or the input is discrete (as in
digital communications) the equalizer parameters may converge to
parameter settings that fail to achieve the objective of approximating
the channel inverse. It is also shown that a center spike initialization
is insufficient to guarantee avoiding such ill-convergence. Simulations
verify the analytical results
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