Reducing the Number of Computations in Stack Decoding of Convolutional Codes by Exploiting Symmetries of the Encoder

摘要

A method of decoding of convolutional codes is described, where the decoding algorithm looks for an information-vector correction sequence, that must be added to the inverse of the received data vector sequence. This is in contrast with the usual method, tries to estimate the information vector sequence directly. Both methods are equally complex for a maximum likelihood (ML) decoder. In sequential decoding, with hard as well as with soft decisions, symmetries of the code can be exploited to reduce the number of computations and hence, the erasure probability. This is illustrated by simulation results. The method is similar to the use of state space symmetries of the syndrome former to obtain a reduction in the exponential rate of growth of the hardware of a Viterbi-like syndrome decoder.