Novel scarce-state-transition syndrome-former error-trellisdecoding of (n, n-1) convolutional codes

摘要

A novel maximum-likelihood hard- and 8-level soft-decisionscarce-state-transition (SST) type syndrome-former error-trellisdecoding system of (n,n-l) convolutional codes with coherent BPSKsignals for additive white Gaussian noise channels is proposed. Theproposed system retains the same number of binary comparisons as thesyndrome-former trellis decoding method of Yamada et al. (1983). Likethe original SST-type register-exchange Viterbi decoding system, theproposed system also has the same advantage of drawing less power whenimplemented on CMOS LSI chips. A combination of the two techniquesresults in a less complex and low power consumption decodingsystem