Optimization of Iterative Decoding for Polar Product Codes
To improve the error-correction performance of polar product codes, this paper designs an optimization criterion for the weighted factors (WFs) in the iterative decoding. Firstly, a weighted mean square error criterion is proposed to optimize the WFs. Secondly, this criterion for optimizing the WFs is extended to polar and single parity-check turbo product code (P&SPC-TPC) and polar turbo product code (Polar-TPC). The optimized WFs obtained according to this criterion are superior to those obtained from Monte Carlo simulations. The two optimized iterative decoders of TPCs, P&SPC-TPC and Polar-TPC, can obtain noticeable performance gains compared with the original product decoders.
Authors
- Yimeng Liu (ORCID: https://orcid.org/0000-0001-9323-4575)
- Yangmin Li (ORCID: https://orcid.org/0000-0002-4448-3310)
- Yue Xu (ORCID: https://orcid.org/0000-0001-7672-9170)
- Ming Jiang (ORCID: https://orcid.org/0000-0001-9952-6990)
Institutions
- Purple Mountain Laboratories (CN)
- Southeast University (CN)
Publication Details
- Published
- 2024-08-21
- DOI
- https://doi.org/10.1109/apwcs61586.2024.10679318
- Primary Topic
- Algorithms and Data Compression
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China