(To be removed) Equalize signal using equalizer object
equalize will be removed in a future release. Use comm.LinearEqualizer or comm.DecisionFeedback instead.
y = equalize(eqobj,x)
y = equalize(eqobj,x,trainsig)
[y,yd] = equalize(...)
[y,yd,e] = equalize(...)
y = equalize(eqobj,x) processes the baseband
signal vector x with equalizer object eqobj and
returns the equalized signal vector y. At the end of the process,
eqobj contains updated state information such as equalizer weight
values and input buffer values. To construct eqobj, use the
lineareq or dfe function. The
equalize function assumes that the signal x
is sampled at nsamp samples per symbol, where
nsamp is the value of the nSampPerSym property
of eqobj. For adaptive algorithms other than CMA, the equalizer
adapts in decision-directed mode using a detector specified by the
SigConst property of eqobj. The delay of the
equalizer is (eqobj.RefTap-1)/eqobj.nSampPerSym.
Note that (eqobj.RefTap-1) must be an integer multiple of
nSampPerSym. For a fractionally-spaced equalizer, the taps are
spaced at fractions of a symbol period. The reference tap pertains to training symbols,
and thus, must coincide with a whole number of symbols (i.e., an integer number of
samples per symbol). eqobj.RefTap=1 corresponds to the first symbol,
eqobj.RefTap=nSampPerSym+1 to the second, and so on. Therefore
(eqobj.RefTap-1) must be an integer multiple of
nSampPerSym.
If eqobj.ResetBeforeFiltering is 0,
equalize uses the existing state information in
eqobj when starting the equalization operation. As a result,
equalize(eqobj,[x1 x2]) is equivalent to
[equalize(eqobj,x1) equalize(eqobj,x2)]. To reset
eqobj manually, apply the reset function to
eqobj.
If eqobj.ResetBeforeFiltering is 1,
equalize resets eqobj before starting the
equalization operation, overwriting any previous state information in
eqobj.
y = equalize(eqobj,x,trainsig) initially
uses a training sequence to adapt the equalizer. After processing the training sequence,
the equalizer adapts in decision-directed mode. The vector length of
trainsig must be less than or equal to
length(x)-(eqobj.RefTap-1)/eqobj.nSampPerSym.
[y,yd] = equalize(...) returns the vector
yd of detected data symbols.
[y,yd,e] = equalize(...) returns the result
of the error calculation. For adaptive algorithms other than CMA, e
is the vector of errors between y and the reference signal, where the
reference signal consists of the training sequence or detected symbols.