A Class of Staircase Codes With Mixed Components and Its Low-Complexity Decoding
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作者:
Zhu, Mingyang
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Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
Purple Mt Labs, Nanjing, Peoples R ChinaSoutheast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
Zhu, Mingyang
[1
,2
]
Jiang, Ming
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Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
Purple Mt Labs, Nanjing, Peoples R ChinaSoutheast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
Jiang, Ming
[1
,2
]
Zhao, Chunming
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Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
Purple Mt Labs, Nanjing, Peoples R ChinaSoutheast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
Zhao, Chunming
[1
,2
]
机构:
[1] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
In this paper, we study a class of staircase codes (SCCs), which is constructed by algebraic and single-parity-check component codes. These codes are referred to as mixed-component SCCs (MC-SCCs). We propose a low-complexity ternary message passing decoding algorithm for MC-SCCs, where error-and-erasure decoding plays a core role and soft reliability is reconstructed by hard decisions and channel log-likelihood ratios. We develop the density evolution analysis that is applicable to both binary and non-binary algebraic codes to optimize the decoder. By properly selecting mixed components, we can construct low-error-floor MC-SCCs with a smaller size of decoding window (proportional to component lengths) and a faster speed of convergence compared with the conventional SCCs. Moreover, we verify that for various requirements of overhead and decoding window size, MC-SCCs can outperform the conventional SCCs with both BCH components in terms of both error-rate performance and decoding complexity.
机构:
Sun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510006, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510006, Guangdong, Peoples R China
Cai, Suihua
Lin, Nina
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Sun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510006, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510006, Guangdong, Peoples R China
Lin, Nina
Ma, Xiao
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机构:
Sun Yat Sen Univ, Guangdong Key Lab Informat Secur Technol, Guangzhou 510006, Guangdong, Peoples R China
Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou 510006, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510006, Guangdong, Peoples R China
机构:
Sun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510006, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510006, Guangdong, Peoples R China
Cai, Suihua
Lin, Nina
论文数: 0引用数: 0
h-index: 0
机构:
Sun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510006, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510006, Guangdong, Peoples R China
Lin, Nina
Ma, Xiao
论文数: 0引用数: 0
h-index: 0
机构:
Sun Yat Sen Univ, Guangdong Key Lab Informat Secur Technol, Guangzhou 510006, Guangdong, Peoples R China
Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou 510006, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510006, Guangdong, Peoples R China