Adaptive Normalized Min-Sum Decoding Algorithm For LDPC Codes in Flash Memory

For globally coupled low density parity check (GCLDPC) codes, the normalized Min-Sum (NMS) algorithm is a widely-used decoding algorithm but suffers from the degraded performance and the slow convergence speed. To address this issue, in this paper, by analyzing the relation between the bit error rat...

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Vydáno v:2025 IEEE/CIC International Conference on Communications in China (ICCC) s. 1 - 6
Hlavní autoři: Yu, Min, Zhai, Xiongfei, Hu, Mengxin, Tao, Shunyou, Fang, Yi, Han, Guojun
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 10.08.2025
Témata:
adaptive normalized factor
AWGN channels
Convergence
Decoding
Flash memories
GC-LDPC codes
Heuristic algorithms
Iterative decoding
NMS algorithm
Simulation
two-level decoding
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Abstract For globally coupled low density parity check (GCLDPC) codes, the normalized Min-Sum (NMS) algorithm is a widely-used decoding algorithm but suffers from the degraded performance and the slow convergence speed. To address this issue, in this paper, by analyzing the relation between the bit error ratio (BER) and the degree of polarization of log-likelihood ratio (LLR) information, we propose an adaptive NMS decoding algorithm. In particular, the normalized factor is dynamically adjusted based on the average LLR information in the initial and the current iterations. Besides, the two-level decoding scheme is considered. Simulation results show that, in the additive white Gaussian noise (AWGN) channels and the flash memory channels, as compared with the NMS algorithm, our algorithm significantly improves the decoding performance and the convergence speed.
AbstractList For globally coupled low density parity check (GCLDPC) codes, the normalized Min-Sum (NMS) algorithm is a widely-used decoding algorithm but suffers from the degraded performance and the slow convergence speed. To address this issue, in this paper, by analyzing the relation between the bit error ratio (BER) and the degree of polarization of log-likelihood ratio (LLR) information, we propose an adaptive NMS decoding algorithm. In particular, the normalized factor is dynamically adjusted based on the average LLR information in the initial and the current iterations. Besides, the two-level decoding scheme is considered. Simulation results show that, in the additive white Gaussian noise (AWGN) channels and the flash memory channels, as compared with the NMS algorithm, our algorithm significantly improves the decoding performance and the convergence speed.
Author Hu, Mengxin
Fang, Yi
Zhai, Xiongfei
Han, Guojun
Yu, Min
Tao, Shunyou
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  organization: Guangdong University of Technology,School of Information Engineering,Guangzhou,China,510006
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Snippet For globally coupled low density parity check (GCLDPC) codes, the normalized Min-Sum (NMS) algorithm is a widely-used decoding algorithm but suffers from the...
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SubjectTerms adaptive normalized factor
AWGN channels
Convergence
Decoding
Flash memories
GC-LDPC codes
Heuristic algorithms
Iterative decoding
NMS algorithm
Simulation
two-level decoding
Title Adaptive Normalized Min-Sum Decoding Algorithm For LDPC Codes in Flash Memory
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