Uppsala universitet

Robust Decision Feedback Equalizers

Mikael Sternad , Anders Ahlén and Erik Lindskog

IEEE International Conference on Acoustics, Speech and Signal Processing, Minneapolis, MN, vol III, pp 555-558, April 27-30, 1993. © 1993 IEEE.

Paper In Pdf.

When digital data are transmitted over dispersive radio channels, a Decision Feedback Equalizer (DFE) can be utilized to estimate transmitted symbols. The paper presents a model-bases methodology for robust design, aimed at reducing the effect of model uncertainties and of decision errors in the feedback loop.

Design equations are presented for robust and realizable decision feedback equalizers, based on uncertain models of IIR channels with coloured noise. Given a probabilistic measure of model uncertainty, the MSE, averaged over a whole class of possible channel models and noise models, is minimized.

A second type of robustification, which reduces the error propagation due to the feedback, is also introduced: the design is optimized under the assumption that previous decisions are affected by white noise. When the variance of this noise is increased, the gain of the DFE feedback filter is reduced. In the limit, we obtain a recursive linear equalizer which minimizes the model-averaged MSE. By treating the decisioned data as uncertain, the length of error bursts due to feedback is reduced. Simpler coding schemes, which use less interleaving, can then be used. For some channels, the probability of decision errors can also be reduced significantly by selecting a nonzero noise variance.

The resulting design equations define a large class of equalizers, with DFE's and linear equalizers based on nominal models being special cases.

Related publications:
PhD Thesis by Erik Lindskog, which explains "self-robustification" of DFE's.
Licentiate Thesis by Erik Lindskog, May 1995, which includes the paper.
Robustification against time-variations within a GSM TDMA frame.
Robust filter design and uncertainty modelling, as described in Automatica 1993.
PhD Thesis by Kenth Öhrn May 1996, describing robust filter design in detail.

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