Memory savings in Viterbi decoders for (n, 1, m) convolutional codes

A novel approach to achieve memory savings in MLD Viterbi decoders is proposed. It is based on tracking a code's trellis survivor paths in the decoding decision process using a backward labels technique, rather than the traditional forward labels technique, and exploiting a 'shift register' property of the trellis. Savings of the order of 20% of memory requirements in (n, 1, m) convolutional codes are achievable without loss of decoding performance.