• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.181-186
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• 2004

Recently, there has been intensive focus on Turbo Product Codes(TPCs) which have low decoding complexity and achieve near-optimum performances at high code-rate. This paper present a parallel algorithm of turbo product codes enable simultaneous decoding of row and column. The row and column decoders operate in parallel and update each other after row and column has been decoded. simulation results show that the performance of proposed parallel turbo code is almost the same as that conventional scheme for several turbo product codes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.442-449
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• 2005

In this paper, we introduce three kinds of simplified high-speed decoding algorithms for turbo product decoder. First, A parallel decoder structure, the row and column decoders operate in parallel, is proposed. Second, HAD(Hard Decision Aided) algorithm is used for early-stopping algorithm. Lastly, P-Parallel TPC decoder is a parallel decoding scheme, processing P rows and P columns in parallel instead of decoding one by one as that in the original scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.205-215
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• 2007

This paper presents low latency and/or computation algorithms of iterative codes of turbo codes, turbo product codes and low density parity check codes for use in wireless broadband communication systems. Due to high coding complexity of iterative codes, this paper focus on lower complexity and/or latency algorithms that are easily implementable in hardware and further accelerate the decoding speed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1095-1102
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• 2016

In this paper, we propose a decoding scheme that can apply to a three dimensional turbo product code(TPC) with a single parity check code(SPC). In general, SPC is used an axis with shortest code length in order to maximize a code rate of the TPC. However, SPC does not have any error correcting capability, therefore, the error correcting capability of the three-dimensional TPC results in little improvement in comparison with the two-dimensional TPC. We propose two schemes to improve performance of three dimensional TPC decoder. One is $min^*$-sum algorithm that has advantages for low complexity implementation compared to Chase-Pyndiah algorithm. The other is a modified serial iterative decoding scheme for high performance. In addition, the simulation results for the proposed scheme are shown and compared with the conventional scheme. Finally, we introduce some practical considerations for hardware implementation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.216-225
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• 2007

This paper presents bit splitting methods to apply multilevel modulation to iterative codes such as turbo code, low density parity check code and turbo product code. Log-likelihood ratio method splits multilevel symbols to bits using the received in-phase and quadrature component based on Gaussian approximation. However it is too complicate to calculate and implement hardware due to exponential and log calculation. therefore this paper presents Euclidean, MAX and Sector method to reduce the high complexity of LLR method. We propose optimal bit splitting method for three iterative codes.

• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.1026-1035
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• 2011

This paper presents generalization and application for the conventional SISO decoding algorithm of Block Turbo Codes. R. M. Pyndiah suggested an iterative SISO decoding algorithm for Product Codes, two-dimensionally combined linear block codes, on AWGN channel. It wascalled Block Turbo Codes. Based on decision of Chase algorithm which is SIHO decoding method, SISO decoder for BTC computes soft decision information and transfers the information to next decoder for iterative decoding. Block Turbo Codes show Shannon limit approaching performance with a little iteration at high code rate on AWGN channel. In this paper we generalize the conventional decoding algorithm of Block Turbo Codes, under BPSK modulation and AWGN channel transmission assumption, to the LLR value based algorithm and suggest an application example such as concatenated structure of LDPC codes and Block Turbo Codes.

• 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.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.11a
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• pp.282-282
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• 2004

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10C
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• pp.758-763
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• 2008

We introduce a noise-predictive turbo equalization using noise filter in perpendicular magnetic recording(PMR) channel. The noise filter mitigates the colored noise in high-density PMR channel. In this paper, the channel detectors used are SOVA (Soft Output Viterbi Algorithm) and BCJR algorithm which proposed by Bahl et al., and the outer decoder used is LDPC (Low Density Parity Check) code that is implemented by sum-product algorithm. Two kinds of LDPC codes are experimented. One is the 0.5Kbyte (4336,4096) LDPC code with the code rate of 0.94, and the other is 1Kbyte (8432,8192) LDPC code with the code rate of 0.97.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1654-1665
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• 2008

This paper presents bit splitting methods to apply multilevel modulation to iterative codes such as turbo code, low density parity check code and turbo product code. Log-likelihood ratio method splits multilevel symbols to soft decision symbols using the received in-phase and quadrature component based on Gaussian approximation. However it is too complicate to calculate and to implement hardware due to exponential and logarithm calculation. Therefore this paper presents Euclidean, MAX, sector and center focusing method to reduce the high complexity of LLR method. Also, this paper proposes optimal soft symbol split method for three kind of iterative codes. Futhermore, 16-APSK modulator method with double ring structure for applying DVB-S2 system and 16-QAM modulator method with lattice structure for T-DMB system are also analyzed.