mohatta2015.pdf

THE LITERATURE 111
both directions and then selecting the direction with smaller errors was proposed in
[Hig89]. This approach can be refined to select (arbitrate) the direction separately
for each symbol using a local Euclidean distance metric [Nel05]. (Replacing the local
metric with MLSD [Bot08] leads to a form of assisted MLSD, which is discussed in
the next chapter.) Decoder feedback can improve the arbitration process [Oh07].
Another solution is to apply linear pre-filtering to convert the channel to minimum
phase. As the DFE is usually designed assuming white noise, the pre-filter
should be an all-pass filter so as not to color the noise. Early work on pre-filtering
for DFE can be found in [Mar73]. More references on pre-filtering are given in the
next chapter.
We have assumed sufficient taps in the FF. If the number of taps is limited, then
various tap selection approaches can be used. These are discussed in the previous
chapter.
A number of solutions have been proposed to address error propagation. One
approach is to improve the feedback using the following.
1. Erase unreliable decisions [Chi98, Fan99].
2. Use a soft MMSE symbol estimate [GerOO, ArsOla]. This can be related to
neural network processing [GerOO].
3. Use multiple hard symbol values when the decision variable is small in magnitude
[Dah88]. This can be done by having multiple DFEs, each feeding back
a different detected value. An accumulated error can be used to select which
DFE to use for the final detected value and further decisions. This can be
interpreted as a form of arbitration in which the two DFEs process data in
the same direction.
4. In a coded system, error propagation can be reduced by using decoder feedback
to improve the decisions [Koh86, San96, Ari98].
In the MIMO/cochannel scenario, LE with multiple receive antennas combined
with SIC has been proposed [AriOOb]. Ordering of detection is addressed in [Kim06].
In CDMA, there are a number of DFE forms employed in multiuser detection.
The classic structure of feedforward and feedback filtering can be found in [Abd94,
Due95]. Using tentative decisions for future symbol periods as well is discussed
in [Xie90a]. A subset of the users can be suppressed linearly rather than being
subtracted [Woo02].
A related approach found in the multiuser detection literature is successive interference
cancellation (SIC), in which symbols are detected one at a time. Early
work can be found in [Den93]. Repeating the process, so that the first symbol benefits
from ISI removal as well, gives rise to multistage SIC. If we detect all symbols
without ISI removal in the first stage, this gives rise to multistage parallel interference
cancellation (PIC) [Div98]. Early work can be found in [Mas88]. Use of
different nonlinearities in SIC and PIC is explored in [TanOla, Zha03]. A mixture
of SIC and PIC can also be used [Kou98]. Note: If we remove the decision nonlinearity
and use decision variables for subtraction, we end up with a form of block
linear equalization in which the matrix equation of final decision variables is being