Maximum likelihood convolutional decoder

Abstract

A maximum likelihood decoding system includes a branch metric processor which calculates only one of four branch metrics associated with branches leading to two consecutive states S.sub.j and S.sub.+1, where j is even. The system determines the remaining three metrics by producing a second branch metric by manipulating the first branch metric using simple binary operations and assigns the first and second metrics to the second and first branches, respectively, leading to the odd state. The system next retrieves associated path metrics from a path metric memory which stores the information in locations accessed by addresses related to identifiers associated with the branch initial states. After the system selects a surviving path for each end state, it stores in a path memory location associated with the end state information identifying the previous state on the surviving path. Thereafter, during trace back, the system uses the identifier of a known end state to address the path memory and retrieve the information identifying a previous state on the path. The system assigns data values to the branches of the most likely path as soon as it identifies the states on the path, since all branches leading to an even state are associated with a 'ZERO' data bit and all branches leading to an odd state are associated with a 'ONE' data bit.