• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.210-219
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• 2017

This paper proposes a modified min-max algorithm (MMMA) for nonbinary quasi-cyclic low-density parity-check (NB-QC-LDPC) codes and an efficient parallel block-layered decoder architecture corresponding to the algorithm on a graphics processing unit (GPU) platform. The algorithm removes multiplications over the Galois field (GF) in the merger step to reduce decoding latency without any performance loss. The decoding implementation on a GPU for NB-QC-LDPC codes achieves improvements in both flexibility and scalability. To perform the decoding on the GPU, data and memory structures suitable for parallel computing are designed. The implementation results for NB-QC-LDPC codes over GF(32) and GF(64) demonstrate that the parallel block-layered decoding on a GPU accelerates the decoding process to provide a faster decoding runtime, and obtains a higher coding gain under a low $10^{-10}$ bit error rate and low $10^{-7}$ frame error rate, compared to existing methods.

• ETRI Journal
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• v.31 no.5
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• pp.510-517
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• 2009

A high throughput parallel decoding method is developed for context-based adaptive variable length codes. In this paper, several new design ideas are devised and implemented for scalable parallel processing, a reduction in area, and a reduction in power requirements. First, simplified logical operations instead of memory lookups are used for parallel processing. Second, the codes are grouped based on their lengths for efficient logical operation. Third, up to M bits of the input stream can be analyzed simultaneously. For comparison, we designed a logical-operation-based parallel decoder for M=8 and a conventional parallel decoder. High-speed parallel decoding becomes possible with our method. In addition, for similar decoding rates (1.57 codes/cycle for M=8), our new approach uses 46% less chip area than the conventional method.

• ETRI Journal
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• v.35 no.5
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• pp.767-774
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• 2013

In this paper, a novel parallel Viterbi decoding scheme is proposed to decrease the decoding latency and power consumption for the software-defined radio (SDR) system. It implements a divide-and-conquer approach by first dividing a block into a series of subblocks, then performing independent Viterbi decoding for each subsequence, and finally merging the surviving subpaths into the final path. Moreover, a network-on-chip-based SDR platform is used to evaluate the performance of the proposed parallel Viterbi decoding scheme. The experiment results show that our scheme can speed up the Viterbi decoding process without increasing the BER, and it performs better than the current state-of-the-art methods.

• Journal of the Korea Society for Simulation
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• v.14 no.4
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• pp.87-93
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• 2005

In this paper we propose a new iterative decoding method of turbo code which computes the log-likelihood ratios at each MAP (maximum a posteriori) decoder in parallel in each iteration step and combines them with proper weights to produce better decisions. Our results indicate that the proposed decoding method is particularly useful for systems with limited number of iterations and low code rates.

• Journal of IKEEE
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• v.11 no.4
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• pp.198-204
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• 2007

For parallel and serially concatenated trellis coded modulation (TCM), improved iterative decoding schemes with a simple mechanism are proposed and their performances are compared with those of conventional decoding schemes. Simulation results have shown that the proposed schemes have provided a considerable decoding gain in additive white Gaussian noise (AWGN) channels and Rayleigh fading channels, even if they can be implemented by a simple modification of conventional decoding algorithms.

• 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.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.450-456
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• 2005

In this paper, we propose a high-speed turbo decoding algorithm and present results of its implementation. The latency caused by (de)interleaving and iterative decoding in conventional MAP turbo decoder can be dramatically reduced with the proposed scheme. The main cause of the time reduction is to use radix-4, center to top, and parallel decoding algorithm. The reduced latency makes it possible to use turbo decoder as a FEC scheme in the real-time wireless communication services. However the proposed scheme costs slight degradation in BER performance because the effective interleaver size in radix-4 is reduced to an half of that in conventional method. To ensure the time reduction, we implemented the proposed scheme on a FPGA chip and compared with conventional one in terms of decoding speed. The decoding speed of the proposed scheme is faster than conventional one at least by 5 times for a single iteration of turbo decoding.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.11
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• pp.35-43
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• 2008

A new effective parallel decoding method has been developed for context-based adaptive variable length codes. In this paper, several new design ideas have been devised for scalable parallel processing, less area, and less power. First, simplified logical operations instead of memory look-ups are used for fast low power operations. Second the codes are grouped based on their lengths for efficient logical operation. Third, up to M bits of input are simultaneously analyzed. For comparison, we have designed the logical operation based parallel decoder for M=8 and a typical conventional method based decoder. High speed parallel decoding is possible with our method. For similar decoding rates (1.57codes/cycle for M=8), our new approach uses 46% less area than the typical conventional method.

• 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.