Trellis state aggregation for soft decoding of variable length codes

Abstract

This paper describes a new set of state models for soft decoding of variable length codes. A single parameter T allows to trade complexity against estimation accuracy. The extrema choices for this parameter lead respectively to construct the well-known bit-level and bit/symbol trellises. For a proper choice of the parameter T, the results obtained by running a BCJR or Viterbi estimation algorithm on the proposed state models are close to those obtained with the optimum state model. The complexity is however significantly reduced. It can be further decreased by projecting the state model on two state models of reduced size, and by combining their decoding results. This combination is shown to be optimal for the Viterbi algorithm.