2020/04/30 by Chentao Yue, Mahyar Shirvanimoghaddam, Branka Vucetic +1 · 63 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #Algorithm #Algorithms and Data Compression #Block code #Computer science #Concatenated error correction code #Decoding methods #Error Correcting Code Techniques #Fractal and DNA sequence analysis #List decoding #Mathematics #Sequential decoding #Statistics #Theoretical computer science #cs.IT #math.IT
paper · pdf · doi:10.1109/tit.2021.3078575
published in IEEE Transactions on Information Theory 67(7), 4288-4337 (Institute of Electrical and Electronics Engineers) · accepted by IEEE Transactions on Information Theory
arxiv created 2021/05/07 · arxiv updated 2021/05/10 · openalex publication_date 2021/05/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
This paper revisits the ordered statistics decoding (OSD). It provides a comprehensive analysis of the OSD algorithm by characterizing the statistical properties, evolution and the distribution of the Hamming distance and weighted Hamming distance from codeword estimates to the received sequence in the reprocessing stages of the OSD algorithm. We prove that the Hamming distance and weighted Hamming distance distributions can be characterized as mixture models capturing the decoding error probability and code weight enumerator. Simulation and numerical results show that our proposed statistical approaches can accurately describe the distance distributions. Based on these distributions and with the aim to reduce the decoding complexity, several techniques, including stopping rules and discarding rules, are proposed, and their decoding error performance and complexity are accordingly analyzed. Simulation results for decoding various eBCH codes demonstrate that the proposed techniques can significantly reduce the decoding complexity with a negligible loss in the decoding error performance.