MAXIMUM LIKELIHOOD TWO-WAY PRIORITY SEARCH ALGORITHM FOR TAIL-BITING CONVOLUTIONAL CODE

摘要

A maximum likelihood two-way priority search algorithm for a tail-biting convolutional code, said algorithm comprising the following steps: (A) a backward two-way priority search algorithm guided by path metrics of a backward path is applied in a backward manner to a grid T of an auxiliary super-code (I); (B) a forward two-way priority search algorithm guided by precise path metrics of a forward path is applied to all grids of a convolutional code (II). The advantageous effects of the present algorithm are: the decoding complexity has a significantly smaller standard deviation, and the average decoding complexity is significantly better than all other decoding algorithms.