Is this scheme as simple as doing an LMS decision-directed equalization
scheme where the Viterbi algorithm used to make the symbol decision?
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isaacgerg wrote:
Is this scheme as simple as doing an LMS decision-directed equalization
scheme where the Viterbi algorithm used to make the symbol decision?
No there is no “equalizer” per se. It is a misnomer, but a popular one.
What you have is a model of the filter the channel applies to the data
symbols emitted by the source to produce the signal. You do dynamic
programming forward in time over the putative symbols and the metric is
the distance between the observed data and the filter applied to the
paths in reverse. So the channel filter is applied to the “paths” as you
try new symbols. Just like viterbi decoding, you have coalescence. When
all paths backwards terminate in the same node, that is when you emit a
decision in theory. Practically speaking, this is usually done after a
fixed interval.
The channel sounding symbols are used to update the “channel filter”.
This is much better than trying to “invert the channel” which is what an
equalizer does. Those places where the channel transfer function has a
zero in its spectrum (or a deep null) you have significant difficulties
when inverting. You enhance the noise there because you are “nearly
dividing by zero”.
Bob
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ARRL SDR Working Group Chair. Member: ARRL, AMSAT, AMSAT-DL,
TAPR, Packrats, NJQRP, QRP ARCI, QCWA, FRC.
“Trample the slow … Hurdle the dead"