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Fast Convergence Decoding Scheme for LDPC Codes

Lin Zhi-guo

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Abstract

We consider the convergence problem of the conventional decoding scheme of Low-Density Parity-Check(LDPC) codes over Additive White Gaussian Noise(AWGN) channels.In this correspondence,we propose a fast convergence decoding scheme based on quantization,which is a comprehensive method of taking advantage of the Layered Belief Propagation(LBP) algorithm,the Offset Min-Sum(OMS) algorithm and the quantization method.Compared to the conventional quantized Min-Sum algorithm,the proposed scheme efficiently reduces the decoding complexity and significantly accelerates the decoding convergence with no additional performance loss.We show that with simulations.

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What this paper is about

We consider the convergence problem of the conventional decoding scheme of Low-Density Parity-Check(LDPC) codes over Additive White Gaussian Noise(AWGN) channels.In this correspondence,we propose a fast convergence decoding scheme based on quantization,which is a comprehensive method of taking advantage of the Layered Belief Propagation(LBP) algorithm,the Offset Min-Sum(OMS) algorithm and the quantization method.Compared to the conventional quantized Min-Sum algorithm,the proposed scheme efficiently reduces the decoding complexity and significantly accelerates the decoding convergence with no additional performance loss.We show that with simulations.

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Available abstract

We consider the convergence problem of the conventional decoding scheme of Low-Density Parity-Check(LDPC) codes over Additive White Gaussian Noise(AWGN) channels.In this correspondence,we propose a fast convergence decoding scheme based on quantization,which is a comprehensive method of taking advantage of the Layered Belief Propagation(LBP) algorithm,the Offset Min-Sum(OMS) algorithm and the quantization method.Compared to the conventional quantized Min-Sum algorithm,the proposed scheme efficiently reduces the decoding complexity and significantly accelerates the decoding convergence with no additional performance loss.We show that with simulations.

Key concepts: Decoding methods, Low-density parity-check code, Additive white Gaussian noise, Algorithm, Belief propagation, Quantization (signal processing), Berlekamp–Welch algorithm, Convergence (economics)

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