A Low Complexity Stack Decoder for a Class of Binary Rate (n-1)/n Convolutional Codes

In this paper we discuss the implementation of a modified stack decoder for a class of binary rate
R = (n - 1)/n
convolutional codes used on a binary symmetric channel (BSC). For large values of
n
, the classical implementation of the stack decoder quickly becomes impractical, as each extension of an information sequence estimate gives rise to
2^{(n-1)}
successor estimates. A Fano type of sequential decoder is then preferable. However, by using the structure of a class of systematic rate
(n - 1)/n
codes, with optimum distance profile (ODP), we are able to modify the classical stack decoder such that it is of comparable complexity. The average number Of stack reorganizations, as well as the average number of successors per extension, can be reduced considerably, without increase of decoding error probability.