We examine the theoretical underpinnings of lexicodes and investigate various generalizations. Our intent is to graft desired decoding properties onto the heuristically good features of lexicodes. In this way, we develop a means for designing good codes for specific tasks. For example, we can fashion good codes which maintain a desired dimension, error-correction capability, and memory constraint.

Section 2 opens with a definition of
the lexicographic construction, which iteratively
constructs generator matrices for the family of
minimum distance *d* lexicodes, for any *d* > 0.
The lexicographic construction is, in turn, a special case
of the generalized lexicographic construction, which we abbreviate
as the
-construction. This generalized construction
encompasses a variety of code families which graft different
properties onto lexicode features.

Section 3 is devoted to various instances of the -construction. Specifically, Section 3.1 analyzes the role of lexicodes as one of these instances and describes tools for efficiently constructing them. In Section 3.2 we demonstrate that a simple modification of the lexicode generator produces ``trellis-oriented'' lexicodes that locally minimize trellis complexity. These codes exhibit the same ``approximately optimal'' features of lexicodes but often have a much lower trellis decoding complexity, in some cases reaching the lowest trellis complexity known for their length, rate, and minimum distance. This modification provides a natural heuristic for transforming a given code into a similar code with (often) a better trellis complexity. Finally, in Section 3.3 we examine methods for designing codes with various trellis characteristics, such as constrained state complexity or constrained Viterbi decoding complexity. These methods might be particularly useful for VLSI-based decoding, where implementation constraints favor a small trellis state complexity, and for mobile communications, where portability severely limits power consumption.

Section 4 investigates the coset relationship which supports the -construction. This relationship establishes bounds on the parameters of the codes produced by the construction and suggests a natural algorithm for computing these codes. The bounds established, though loose, are asymptotically tighter than the lexicode bounds of Brualdi and Pless [3]. We also use the coset relationship to bound the computation time of the -construction in Section 5.

Finally, in Section 6 we discuss various applications of the -construction and present our conclusions. The appendix lists simulation results for the some of the algorithms described in the paper, extending the list of lexicode parameters originally published in [5].