Pre-processing of convolutional codes for reducing decoding power consumption

This paper presents a new pre-processing approach for convolutional codes that can provide the adaptive capability to a standard Viterbi decoder. By identifying and generating the decoded data from the zero Hamming distance path, all computations in the Viterbi decoder can be avoided. This makes it possible to stop the Viterbi decoder in real time as long as no error occurs in the received code words; the Viterbi decoder is restarted to correct errors otherwise. With this approach, significant power, i.e. 97% of a standard Viterbi decoder power dissipation, can be saved when the Eb/No is as low as 13 dB.