Sequential decoding
Open-knowledge reference entry
Recognised by John Wozencraft, sequential decoding is a limited memory technique for decoding tree codes. Sequential decoding is mainly used as an approximate decoding algorithm for long constraint-length convolutional codes. This approach may not be as accurate as the Viterbi algorithm but can save a substantial amount of computer memory. It was used to decode a convolutional code in 1968 Pioneer 9 mission.
Sequential decoding explores the tree code in such a way to try to minimise the computational cost and memory requirements to store the tree.
There is a range of sequential decoding approaches based on the choice of metric and algorithm. Metrics include:
Fano metric
Zigangirov metric
Gallager metric
Algorithms include:
Stack algorithm
Fano algorithm
Creeper algorithm
Fano metric
Given a partially explored tree (represented by a set of nodes which are limit of exploration), we would like to know the best node from which to explore further. The Fano metric (named after Robert Fano) allows one to calculate from which is the best node to explore further. This metric is optimal given no other constraints (e.g. memory).
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