Abstract not found

Absfroct- The trellis complexity of block codes is closely related to their soft-decision decoding complexity. We investigate the trellis properties of composite-length cyclic codes. Trelliis-oriented decompositions are presented, and improved upper bounds on the trellis complexity are derived. I.

Abstruct-The trellis state-complexity s of a linear block code is defined as the logarithm of the maximum number of states in its minimal trellis. We present a new lower bound on the statecomplexity of linear codes, which includes most of the existing bounds as special cases. The new bound

We generalize constructions of lexicographic codes to produce locally optimal codes with a desired trellis decoding complexity. These constructions are efficient for high rate codes and provide a means for automated code design. As a byproduct, we improve known bounds on the parameters of lexicodes.

decoding complexity is locally optimized. We also show how to construct generalized lexicographic codes whose trellis state-complexity satisfies a prescribed bound. Fuller version in IEEE Trans. Inf. Theory, expected 1/2002.

investigated, in the case where the weights of nonzero codewords in g

Abstract not found

An important problem in the theory and application of block code trellises is to find a coordinate permutation of a given code to minimize the trellis complexity. In this paper we show that the problem of finding a coordinate permutation that minimizes the number of vertices at a given depth

for high data rate wireless communication. The encoding/decoding complexity of these codes is comparable to trellis codes employed in practice over Gaussian channels. The codes constructed here provide the best tradeoff between data rate, diversity advantage, and trellis complexity. Simulation results

sub optimal and iterative decoding techniques. key words: trellises, tail-biting trellis, mutual information, maximum-likelihood decoding, Viterbi algorithm 1. Introduction The notion of tail-biting wa soriginafi) conceived by Solomonal va n Tilborg [12] to convolutiona(Y encode ae decode quajfi