Low complexity algorithm for the decoding of convolutional codes of any rate

It is well known that convolutional codes can be optimally decoded by using the Viterbi algorithm (VA). A decoding technique where the VA is applied to identify the error vector rather than the information message is proposed. We previously focused on convolutional coders of rate 1/2 . The method to codes of any rate is generalized and shows that, with the proposed type of decoding, the exhaustive computation of a vast majority of state to state iterations is unnecessary. Hence, performance close to optimum is achievable with a significant reduction of complexity. The higher the SNR, the greater the improvement for reduction in complexity. For instance, for SNR greater than 3 dB, a five fold reduction in complexity for the computation of ACS (add compare select) is achieved.