The Structure and Design of Realizable Decision Feedback
Equalizers for IIR Channels with Coloured Noise
IEEE Transactions on Information
vol IT-36, pp 848-858, July 1990.
© 1990 IEEE.
Also: Internal Report UPTEC 8864R, Dept. of Technology,
Report, without figures, available in Postscript :
compressed(gz) 129K ,
With figures In Pdf 816K.
When digital data are transmitted over a dispersive channel,
a decision feedback equalizer can be utilized to estimate
This detector subtracts an estimate of the intersymbol interference
caused by previous symbols, before making symbol-by-symbol
decisions. The paper discusses the model-based
design of the filters included in the device.
A simple algorithm for optimizing decision feedback equalizers
by minimizing the mean square error (MSE) is presented.
A complex baseband channel and correct past
decisions are assumed. The dispersive channel
may have infinite impulse
response and the noise may be coloured. We consider optimal
realizable (stable and finite-lag smoothing) forward and feedback
filters in discrete time. They are parametrized as recursive
filters. In the special case of
transmission channels with finite impulse response and
autoregressive noise, the minimum MSE can be attained with
transversal feedback and forward filters. In general, the
forward part should include a noise-whitening filter (the
inverse noise model).
The finite realizations of the
filters are calculated using a polynomial equation approach
to the linear quadratic optimization problem.
The equalizer is optimized essentially by solving a system of linear
equations Ax=B, where A contains transfer function coefficients
from the channel and noise model.
No calculation of correlations are required with this method.
A simple expression for the minimal MSE is presented. The DFE is
compared to MSE-optimal linear recursive equalizers. Expressions
for the equalizer in the limiting case of infinite
smoothing lags are also discussed.
- Matlab m-file
for model-based design of MSE-optimal IIR Decision
(written by Stefano Bigi):
- Related publications:
by S Bigi, who considers data-based design when the data record
by E Lindskog, where robust design and multiple measurements are
ICASSP'93, on robustness
against model errors and erroneous past decisions.
Multivariable (MIMO) case
with both multiple sensors and multiple users.
on MIMO fractionally spaced DFE's as
DS-CDMA multiuser detectors .
PhD Thesis by L Lindbom 1995,
with MIMO time-varying
DFE for FIR channels in Chap. 7.
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