Four-Level Quantized Soft Information Aided Hard-Decision Decoder for Product-like Codes

@misc{wu2026fourlevel,
  title = {{Four-Level Quantized Soft Information Aided Hard-Decision Decoder for Product-like Codes}},
  author = {Xiaowei Wu and Min Qiu and Yueying Zhan and Lei Yang},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.21187},
  eprint = {2610.21187},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.21187},
}

TY  - UNPB
TI  - Four-Level Quantized Soft Information Aided Hard-Decision Decoder for Product-like Codes
AU  - Xiaowei Wu
AU  - Min Qiu
AU  - Yueying Zhan
AU  - Lei Yang
PY  - 2026
DA  - 2026/10/15
PB  - arXiv
DO  - 10.48550/arxiv.2610.21187
UR  - https://arxiv.org/abs/2610.21187
AB  - We propose a novel low-complexity soft-aided hard-decision decoding scheme for product-like codes, termed iterative bounded-distance decoding (iBDD) with graded scaled reliability and bit-flipping (GSRF). This scheme operates on four-level quantized soft information. It incorporates a graded scaled reliability rule to assign decoding confidence to the bounded-distance decoding result, and employs a bit-flipping rule based on bit-level and component-code-level reliability. A selective re-decoding rule is designed to further facilitate the error performance while keeping the number of BDD attempts in reasonably low levels. The decoding parameter design of iBDD-GSRF is investigated for product codes and staircase codes, respectively. Simulation results on both codes verify that iBDD-GSRF achieves a gain of more than 0.4 dB over the conventional iBDD, comparable to several existing unquantized soft-aided decoders.
ER  -