![]() According to the algorithm, the process of codeword search continues to move forward along a code path, as long as the Fano metric along the code path remains non-decreasing. Only the path whose path metric is no less than T can be next visited.The movement of the Fano algorithm is guided by a dynamic threshold T that is an integer multiple of a fixed step size Δ.Based on this information, the Fano algorithm can move from the current path to either its immediate predecessor path or the selected successor path hence, no stack is required for queuing all examined paths.At each decoding stage, the Fano algorithm retains the information regarding three paths: the current path, its immediate predecessor path, and one of its successor paths. ![]() The Fano algorithm can only operate over a code tree because it cannot examine path merging.The Fano algorithm is a sequential decoding algorithm that does not require a stack.This algorithm explores backwards and forward from a single point on the tree. The famous Fano algorithm (named after Robert Fano) has a very low memory requirement and hence is suited to hardware implementations. memory).įor a binary symmetric channel (with error probability p or more highly scoring paths above it at this point the best path will drop off the stack and be no longer considered. This metric is optimal given no other constraints (e.g. The Fano metric (named after Robert Fano) allows one to calculate from which is the best node to explore further. 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. There is a range of sequential decoding approaches based on the choice of metric and algorithm. Sequential decoding explores the tree code in such a way to try to minimise the computational cost and memory requirements to store the tree. It was used to decode a convolutional code in 1968 Pioneer 9 mission. This approach may not be as accurate as the Viterbi algorithm but can save a substantial amount of computer memory. Sequential decoding is mainly used as an approximate decoding algorithm for long constraint-length convolutional codes. Recognised by John Wozencraft, sequential decoding is a limited memory technique for decoding tree codes.
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