• ETRI Journal
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• v.28 no.4
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• pp.453-460
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• 2006

In this article, we introduce a new class of product codes based on convolutional codes, called convolutional product codes. The structure of product codes enables parallel decoding, which can significantly increase decoder speed in practice. The use of convolutional codes in a product code setting makes it possible to use the vast knowledge base for convolutional codes as well as their flexibility in fast parallel decoders. Just as in turbo codes, interleaving turns out to be critical for the performance of convolutional product codes. The practical decoding advantages over serially-concatenated convolutional codes are emphasized.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.512-521
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• 2012

In this paper, we propose feasible combining rules for a decoding scheme of product codes to apply finite soft decision. Since the decoding scheme of product codes are based on complex tanh calculation with infinite soft decision, it requires high decoding complexity and is hard to practically implement. Thus, simple methods to construct look-up tables for finite soft decision are derived by analyzing the operations of the scheme. Moreover, we focus on using convolutional codes, which is popular for easy application of finite soft decision, as the horizontal codes of product codes so that the proposed decoding scheme can be properly implemented. Numerical results show that the performance of the product codes with convolutional codes using 4-bit soft decision approaches to that of same codes using infinite soft decision.

• Smart Media Journal
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• v.2 no.2
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• pp.39-43
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• 2013

In this paper, we suggest a new technique for WPC parity-check matrix (H-matrix) generation and a corresponding decoding process. The key idea is to construct WPC H-matrix by using a convolutional encoder. It is easy to have many different coderates from a mother code with convolutional codes. However, it is difficult to have many different coderates with LDPC codes. Constructing LDPC Hmatrix based on a convolutional code can easily bring the advantage of convolutional codes to have different coderates. Moreover, both LDPC and convolutional decoding algorithms can be applied altogether in the decoding part. This process prevents the performance degradation of short-length WPC code.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7C
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• pp.611-617
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• 2010

In this paper, we investigate the performances of the serial concatenated convolutional codes (SCCC) and low-density parity-check (LDPC) codes on perpendicular magnetic recording (PMR) channels. We discuss the performance of two systems when user bit-densities are 1.7, 2.0, 2.4 and 2.8, respectively. The SCCC system is less complex than LDPC system. The SCCC system consists of recursive systematic convolutional (RSC) codes encoder/decoder, precoder and random interleaver. The decoding algorithm of the SCCC system is the soft message-passing algorithm and the decoding algorithm of the LDPC system is the log domain sum-product algorithm (SPA). When we apply the iterative decoding between channel detector and the error control codes (ECC) decoder, the SCCC system is compatible with the LDPC system even at the high user bit density.