Two Step SOVA-Based Decoding Algorithm for Tailbiting Codes
arXiv:2501.13606 · doi:10.1109/LCOMM.2009.090810
Abstract
In this work we propose a novel decoding algorithm for tailbiting convolutional codes and evaluate its performance over different channels. The proposed method consists on a fixed two-step Viterbi decoding of the received data. In the first step, an estimation of the most likely state is performed based on a SOVA decoding. The second step consists of a conventional Viterbi decoding that employs the state estimated in the previous step as the initial and final states of the trellis. Simulations results show a performance close to that of maximum-likelihood decoding.
3 pages, 3 figures