초록 ▼

A method and system for decoding tailbiting convolution codes are disclosed. A set of tailbiting convolutional codes is encoded by a convolutional encoder having multiple encoding states. A first starting score is assigned to each of the encoding states. A Viterbi algorithm is then performed once on

A method and system for decoding tailbiting convolution codes are disclosed. A set of tailbiting convolutional codes is encoded by a convolutional encoder having multiple encoding states. A first starting score is assigned to each of the encoding states. A Viterbi algorithm is then performed once on the tailbiting convolutional code to associate an ending score with each of the encoding states. A subset of these encoding states is subsequently selected, within which the ending score of each encoding state meets a certain criterion. The Viterbi algorithm is again performed on the tailbiting convolutional code for each encoding state within the subset to determine the best encoding state as the most likely initial encoding state for the tailbiting convolutional code. A Trellis path of this most likely initial encoding state is utilized to decode the tailbiting convolutional code.

대표청구항 ▼

[ What is claimed is:] [1.]1. A method for decoding tailbiting convolutional codes, wherein said tailbiting convolutional codes, which are encoded by a convolutional encoder, include a plurality of encoding states, said method comprising the steps of:assigning an identical first staring score to eac

[ What is claimed is:] [1.]1. A method for decoding tailbiting convolutional codes, wherein said tailbiting convolutional codes, which are encoded by a convolutional encoder, include a plurality of encoding states, said method comprising the steps of:assigning an identical first staring score to each of a plurality of encoding states of a tailbiting convolutional code;performing a Viterbi algorithm once on all of said encoding states of said tailbiting convolutional code to associate a first ending score with each of said encoding states;performing said Viterbi algorithm again for each of said encoding states having a first ending score meeting a certain criterion to associate a second ending score with each of said encoding states, wherein the number of encoding states having a first ending score that meets the certain criterion equals the number of times said Viterbi algorithm is performed again; anddecoding said tailbiting convolutional code utilizing a Trellis path having as an initial encoding state one of said encoding states having a lowest second ending score.