摘要
This paper presents a new Hard-Input Hard-Output (HIHO) iterative decoding algorithm for Turbo Product Codes (TPC), and especially describes the BCH-TPC codes aiming to alleviate error propagation and lower error floor. This algorithm mainly emp hasizes a decision mechanism for bit-flips, which thoroughly evaluates four different aspects of the decoding process, properly weighs and combines their respective reliability measures, and then employs the combined measure to make a judgment with regard to whether any particular bit should be flipped or not. Simulations result in a very steep Bit Error Rate (BER) curve indicating that a high-level net coding gain can be expected with a reasonable complexity. The simplicity and effectiveness of this HIHO decoding algorithm makes it a p romising candidate for the application in future high-speed fiber optical communications.
This paper presents a new Hard-Input Hard-Output （HIHO） iterative decoding algorithm for Turbo Product Codes （TPC）, and especially describes the BCH-TPC codes aiming to alleviate error propagation and lower error floor. This algo- rithm mainly emphasizes a decision mechanism for bit-flip s, which thoroughly evaluates four different aspects of the decoding process, properly weighs and combines their respective reliability measures, and then employs the combined measure to make a judgment with regard to whether any particular bit should be flipped or not. Simulations result in a very steep Bit Error Rate （BER） curve indica- ting that a high-level net coding gain can be exp ected with a reasonable complexity. The sim- plicity and effectiveness of this HIHO decoding algorithm makes it a promising candidate for the application in future high-speed fiber optical communications.
基金
The authors would like to thank the editor and reviewer for helpful comments on the manuscripts. We also thank for the form support from Huawei Technology Corporations in this research. This work was partially supported by the National Natural Science Foundation of China under Grant No. 61101092.
