Reduced Complexity Viterbi Decoding Based on the M-Algorithm and the Minimal

In this paper we propose sub-optimum, reduced complexity decoding algorithms for convolutional codes. The algorithms are based on the minimal trellis representation for the convolutional code, and on the M algorithm. We analyze both the computational complexity, in terms of arithmetic operations, and the bit error rate performance of the proposed algorithms. Results demonstrate that large complexity reductions can be obtained while achieving a very good performance.