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

A novel maximum-likelihood hard- and 8-level soft-decision scarce-state-transition (SST) type syndrome-former error-trellis decoding system of (n,n-l) convolutional codes with coherent BPSK signals for additive white Gaussian noise channels is proposed. The proposed system retains the same number of binary comparisons as the syndrome-former trellis decoding method of Yamada et al. (1983). Like the original SST-type register-exchange Viterbi decoding system, the proposed system also has the same advantage of drawing less power when implemented on CMOS LSI chips. A combination of the two techniques results in a less complex and low power consumption decoding system