• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.981-989
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• 2015

In a log likelihood ratio(LLR) calculation of the detected symbol, multiple-input multiple-output(MIMO) system applying an optimal or suboptimal algorithm such as a maximum likelihood(ML) detection, sphere decoding(SD), and QR decomposition with M-algorithm Maximum Likelihood Detection(QRM-MLD) suffers from exponential complexity growth with number of spatial streams and modulation order. In this paper, we propose a LLR calculation method with very low complexity in the QRM-MLD based symbol detector for a high order modulation based $N_T{\times}N_R$ MIMO system. It is able to approach bit error rate(BER) performance of full maximum likelihood detector to within 1 dB. We also analyze the BER performance through computer simulation to verify the validity of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.907-910
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• 2010

This paper presents the design of block lengths for irregular low-density parity-check (LDPC) codes based on the maximum variable degree $d_{{\upsilon},max}$. To design a block length, the performance degradation of belief-propagation (BP) decoding performance from upper bounds on the maximum likelihood (ML) decoding performance is used as an important factor. Since for large block lengths, the performance of irregular LDPC codes is very close to the Shannon limit, we focus on moderate block lengths ($5{\times}10^2\;{\leq}\;N\;{\leq}\;4{\times}10^3$). Given degree distributions, the purpose of our paper is to find proper block lengths based on the maximum variable degree $d_{{\upsilon},max}$. We also present some simulation results which show how a block length can be optimized.

• The Journal of the Acoustical Society of Korea
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• v.21 no.2
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• pp.190-198
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• 2002

In general, we have used the Viterbi algorithm of Speech recognition for decoding. But a decoder in speaker verification has to recognize same word of every speaker differently. In this paper, we propose a noble decoding algorithm that could replace the typical Viterbi algorithm for the speaker verification system. We utilize for the proposed algorithm the speaker adaptation algorithms that transform feature vectors into the region of the client' characteristics in the speech recognition. There are many adaptation algorithms, but we take MLLR (Maximum Likelihood Linear Regression) and MAP (Maximum A-Posterior) adaptation algorithms for proposed algorithm. We could achieve improvement of performance about 30% of EER (Equal Error Rate) using proposed algorithm instead of the typical Viterbi algorithm.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.7
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• pp.12-18
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• 1993

We have proposed a soft-decision decoding method for block codes. With careful examinations of the first hard-decision decoded results, The candidate codewords are efficiently searched for. Thus, we can reduce the decoding complexity (the number of hard-decision decodings) and lower the block error probability. Computer simulation results are presented for the (23,12) Golay code. They show that the decoding complexity is considerably reduced and the block error probability is close to that of the maximum likelihood decoder.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.645-648
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• 2004

In this paper, we drive a theoretical performance of complementary code keying (CCK) codes on additive white Gaussian noise (AWGN) channel. The CCK codes can be demodulated by the optimal maximum likelihood decoding method and sub-optimal correlation magnitude decoding algorithm. We calculate the bit error rate (BER) and symbol or codeword error rate (SER) of the CCK codes using the above mentioned two decoding algorithms. To derive the error performance, we use the weigh distributions and cross-correlation distributions of CCK codes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.160-165
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• 2007

In this paper, we propose a novel signal detection method that achieves the maximum likelihood (ML) performance but requires much less computational complexity than the ML detection. When the well-known linear decoding method is used for space-time block coded (STBC) OFDM systems in fast-fading channels, co-channel interference (CCI) as well as inter-carrier interference (ICI) occurs. A maximum likelihood (ML) method can be employed to deal with the CCI; however, its computational complexity is very high. In this paper, we propose a signal detection method for orthogonal space-time coded OFDM systems that achieves the similar error performance as the ML method, but requires much less computational complexity.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.1-5
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• 2008

In this paper, we propose and analyze the AMC (Adaptive Modulation and Coding) system with efficient turbo coded V-BLAST (Vertical-Bell-lab Layered Space-Time) technique. The proposed algorithm adopts extrinsic information from a MAP (Maximum A Posteriori) decoder with iterative decoding as a priori probability in two decoding procedures of V-BLAST scheme; the ordering and the slicing. Also, we consider the AMC system using the conventional turbo coded V-BLAST technique that simply combines the V-BLAST scheme with the turbo coding scheme. And we compare the proposed decoding algorithm to a conventional V-BLAST decoding algorithm and a ML (Maximum Likelihood) decoding algorithm. In addition, we apply a STD (Selection Transmit Diversity) scheme to the systems for better performance improvement. Results indicate that the proposed systems achieve better throughput performance than the conventional systems over the entire SNR range. In terms of transmission rate performance, the suggested system is close in proximity to the conventional system using the ML decoding algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9C
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• pp.771-777
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• 2010

This paper proposes a new signal detection method, called QR-OSIC with Candidates (QOC) method, for spatially multiplexed multiple input multiple output (MIMO) systems. By using the ordered successive interference cancellation (OSIC) algorithm and the maximum likelihood (ML) metric, the proposed method achieves near-ML performance without requiring a large number of candidates. Although the proposed method can be used for both hard and soft decoding systems, it is especially useful for soft decoding systems since the LLR values for all the bits can be efficiently computed without using LLR estimation. The proposed method is also suitable for VLSI implementation since it leads to fixed throughput system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7C
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• pp.594-597
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• 2010

This paper estimates belief-propagation (BP) decoding performance of moderate-length irregular low-density parity-check (LDPC) codes with sphere bounds. We note that for moderate-length($10^3{\leq}N{\leq}4\times10^3$) irregular LDPC codes, BP decoding performance, which is much worse than maximum likelihood (ML) decoding performance, is well matched with one of loose upper bounds, i.e., sphere bounds. We introduce the sphere bounding technique for particular codes, not average bounds. The sphere bounding estimation technique is validated by simulation results. It is also shown that sphere bounds and BP decoding performance of irregular LDPC codes are very close at bit-error-rates (BERs) $P_b$ of practical importance($10^{-5}{\leq}P_b{\leq}10^{-4}$).