I want to design a Decision Feedback Equalizer (DFE) to combat the multipath channel.
Does anyone know some references about the principles of Decision Feedback
Equalizer (DFE) ?
Further, What is the advantages of DFE compared with normal equalizer?
Many thanks
Read Chapter 3, Section 6 of Cioffi's book:
http://web.stanford.edu/group/cioffi/doc/book/chap3.pdf
This will tell you everything you need to know about DFEs.
The basic idea with a DFE is that assuming the channel hasn't drifted too far from the current equaliser coefficient vector, the decoded symbols from the quantisation (decision) stage should be more or less correct (even more so after FEC decoding - there are many interesting combined DFE/FEC decoder schemes). However, there will be some small error between the output of the equaliser and the output of the quantiser. Therefore, we can essentially use the decoded symbols as training data to get a better estimate of the optimal equaliser (either using a zero-forcing or minimum mean squared error approach, the latter offering better performance).
DFEs generally outperform linear equalisers - however, they can be severely perturbed by impulse noise, noise bursts etc, which destroy the assumption of mostly-correct decisions.
Dear
I think this video is interesting.
https://www.youtube.com/watch?v=YfAHa90CND0
Dear Daniel Robert Franklin,
Thank you very much for your good suggestions.
From the reference you given I have understand how the DFE works.
However, I get some problems in channel estimation of LMS. the step size is dfficultly determined probably because of channel impulse response. I an trying to solve it.
Anyway, Thank you for your help again.
Kind regards
Jiajun
Dear Djamel Teguig,
Thank you for the video. It is a good video to explain the my question.
However, the strong accent let me difficultly understand.
Anyway, Thanks to your support.
Kind regards
Jiajun
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