Syndrome Decoding of Convolutional Codes

Abstract

The classical Viterbi decoder recursively finds the trellis path (code word) closest to the received data. Given the received data, the syndrome decoder first forms a syndrome, instead. A recursive algorithm like Viterbi's is used to determine the noise sequence of minimum Hamming weight that can be a possible cause of this syndrome. Given the estimate of the noise sequence, one derives an estimate of the original data sequence. While the bit error probability of the syndrome decoder is no different from that of the classical Viterbi decoder, the syndrome decoder can be implemented using a read only memory (ROM), thus obtaining a considerable saving in hardware.