Shifted Pruning for Path Recovery in List Decoding of Polar Codes
Mohammad Rowshan, Emanuele Viterbo · 2021
In successive cancellation list (SCL) decoding, the tree pruning operation retains the L best paths with respect to a metric at every decoding step. However, the correct path might be among the L worst paths due to imposed penalties. In this case, the correct path is pruned and the decoding process fails. Shifted-pruning (SP) scheme can recover the correct path by additional decoding attempts when decoding fails, in which the pruning window is shifted by L over the bits with high likelihood of the elimination of the correct path, one at a time. In this work, we generalize the scheme by more freedom in shifting the pruning window, aiming to improve the error correction performance in the constrained number of decoding attempts. We also propose a metric for prioritizing the shifting positions.