Fang Cai
Case Western Reserve University
17 Papers
191 Citations
Fang Cai is an academic researcher from Case Western Reserve University. The author has contributed to research in topics: Decoding methods & Low-density parity-check code. The author has an hindex of 7, co-authored 17 publications.
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Papers
Reduced-Complexity Decoder Architecture for Non-Binary LDPC Codes
Xinmiao Zhang,Fang Cai +1 more
TL;DR: A novel check node processing scheme and corresponding VLSI architectures are proposed for the Min-max NB-LDPC decoding algorithm, which aims to store the most reliable v-to-c messages as “compressed” c- to-v messages so the memory requirement of the overall decoder can be substantially reduced.
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Efficient Partial-Parallel Decoder Architecture for Quasi-Cyclic Nonbinary LDPC Codes
Xinmiao Zhang,Fang Cai +1 more
TL;DR: A complete partial-parallel decoder architecture based on the Min-max algorithm is proposed for quasi-cyclic NB-LDPC codes and an overlapped method for the check node processing among different layers is introduced to further speed up the decoding.
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Low-Complexity Reliability-Based Message-Passing Decoder Architectures for Non-Binary LDPC Codes
Xinmiao Zhang,Fang Cai,Shu Lin +2 more
TL;DR: In this article, an iterative hard reliability-based majority-logic decoding (IHRB-MLGD) algorithm was proposed to achieve significant coding gain with small hardware overhead.
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Relaxed Min-Max Decoder Architectures for Nonbinary Low-Density Parity-Check Codes
Fang Cai,Xinmiao Zhang +1 more
TL;DR: A novel relaxed check node processing scheme is proposed for the min-max NB-LDPC decoding algorithm and the complexity of the check nodes processing can be substantially reduced using the proposed scheme.
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Partial-parallel decoder architecture for quasi-cyclic non-binary LDPC codes
Xinmiao Zhang,Fang Cai +1 more
- 14 Mar 2010
TL;DR: This paper proposes a partial-parallel decoder architecture based on the Min-max algorithm for quasi-cyclic NB-LDPC codes and introduces an overlapped method for the check node processing among different layers to further speed up the decoding.
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