For a heuristic decoding optimization, the mapping
may be
used to generate an approximately optimal ``trellis-oriented'' code.
These codes may be constrained further, however, if there is a
particular memory limit m on the decoding space. In this case, the
mapping
may be used to get a reasonably short code
satisfying dimension, error-correcting capability, and decoding memory
constraints. Alternatively, one might wish to find a family of good codes
with a bounded decoding time, in which case the mapping
would be
appropriate. In each of these cases, the
-construction often
provides a code that meets the desired constraints and
which, empirically, tends to have good parameters.
The appendix lists various
-codes,
demonstrating their use in this application. For example
we see in Appendix .1 that
though the trellis-oriented codes have almost identical code parameters
to their lexicode counterparts, they tend to have a much better trellis complexity.
As another example, we can see in Appendix .2
that by sacrificing about 12% of the information rate, we can reduce decoding complexity from the 1024 states
in the (38, 21, 8) lexicode to a mere 64 states in the (43, 21, 8) state-bounded
code. Such a low memory requirement would be ideal for
a VLSI chip or a smart card.