• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.911-918
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• 2013

This study deals with the small sample likelihood based inference for the ratio of two normal variances. The small sample likelihood inference is an approximation method. The signed log-likelihood ratio statistic and the modified signed log-likelihood ratio statistic, which converge to standard normal distribution, are proposed for the normal variance ratio. Through the simulation study, the coverage probabilities of confidence interval and power of the exact, the signed log-likelihood and the modified signed log-likelihood ratio statistic will be compared. A real data example will be provided.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1173-1181
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• 2008

In this paper, when the parameter of interest is the shape parameter in Pareto distribution, we develop likelihood based inference for this parameter. Specially, we develop signed log-likelihood ratio statistic and the modified signed log-likelihood ratio statistic for the shape parameter. It is well-known that as sample size grows, the modified signed log-likelihood ratio statistic converges to standard normal distribution faster than the signed log-likelihood ratio statistic. But the computation of the modified signed log-likelihood statistic is hard or even impossible when the sufficient statistics and the ancillary statistics are not clear. In this case, one can consider an approximation to the modified signed log-likelihood statistic. Specially, when the parameter of interest is informationally orthogonal to the nuisance parameters, we propose the approximate modified signed log-likelihood statistic. Through simulation, we investigate the performances of the proposed statistics with the signed log-likelihood statistic.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1736-1738
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• 2016

In modern digital communication systems adapting high-order modulation and high performance channel code, log-likelihood ratios involving the repeated calculations of the logarithm of sum of exponential functions are necessary for demodulation and decoding. In this paper, the approximation methods called Min and MinC are applied to demodulation and decoding together and their complexity and joint performance are analyzed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.405-409
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• 2009

In this paper, the effects of LLR (Log-Likelihood Ratio) approximation on LDPC (Low-Density Parity-Check) decoder performance are analyzed, and optimal design conditions of LDPC decoder are derived. The min-sum LDPC decoding algorithm which is based on an approximation of LLR sum-product algorithm is modeled and simulated by MATLAB, and it is analyzed that the effects of LLR approximation bit-width and maximum iteration cycles on the bit error rate (BER) performance of LDCP decoder. The parity check matrix for IEEE 802.11n standard which has block length of 1,944 bits and code rate of 1/2 is used, and AWGN channel with QPSK modulation is assumed. The simulation results show that optimal BER performance is achieved for 7 iteration cycles and LLR bit-width of (7,5).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.10
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• pp.841-849
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• 2012

This paper proposes an low-complexity soft-output multiple-input multiple-output (soft-MIMO) detection algorithm for achieving soft-output maximum-likelihood (soft-ML) performance under max-log approximation. The proposed algorithm is based on a parallel tree-search (PTS) applying a channel ordering by a sorted-QR decomposition (SQRD) with altered sort order. The empty-set problem that can occur in calculation of log-likelihood ratio (LLR) for each bit is solved by inserting additional nodes at each search level. Since only the closest node is inserted among nodes with opposite bit value to a selected node, the proposed node insertion scheme is very efficient in the perspective of computational complexity. The computational complexity of the proposed algorithm is approximately 37-74% of that of existing algorithms, and from simulation results for a $4{\times}4$ system, the proposed algorithm shows a performance degradation of less than 0.1dB.

• 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 the Korean Data and Information Science Society
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• v.17 no.2
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• pp.543-557
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• 2006

This paper is concerned with the applicability of the chi-square approximation to the six disparity statistics: the Pearson chi-square, the generalized likelihood ratio, the power divergence, the blended weight chi-square, the blended weight Hellinger distance, and the negative exponential disparity statistic. Three dimensional contingency tables of small and moderate sample sizes are generated to be fitted to all possible hierarchical log-linear models: the completely independent model, the conditionally independent model, the partial association models, and the model with one variable independent of the other two. For models with direct solutions of expected cell counts, point estimates and confidence intervals of the 90 and 95 percentage points of six statistics are explored. For model without direct solutions, the empirical significant levels and the empirical powers of six statistics to test the significance of the three factor interaction are computed and compared.

• ETRI Journal
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• v.41 no.3
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• pp.308-315
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• 2019

Due to its high spectrum efficiency, 64-amplitude phase-shift keying (64-APSK) is one of the primary technologies used in deep space communications and digital video broadcasting through satellite-second generation. However, 64-APSK suffers from considerable computational complexity because of the de-mapping method that it employs. In this study, a low-complexity de-mapping method for (4 + 12 + 20 + 28) 64-APSK is proposed in which we take full advantage of the symmetric characteristics of each symbol mapping. Moreover, we map the detected symbol to the first quadrant and then divide the region in this first quadrant into several partitions to simplify the formula. Theoretical analysis shows that the proposed method requires no operation of exponents and logarithms and involves only multiplication, addition, subtraction, and judgment. Simulation results validate that the time consumption is dramatically decreased with limited degradation of bit error rate performance.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.939-947
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• 2010

The LDPC(Low-Density Parity-Check) code, which is one of the channel encoding methods in IEEE 802.11n wireless LAN standard, has superior error-correcting capabilities. Since the hardware complexity of LDPC decoder is high, it is very important to take into account the trade-offs between hardware complexity and decoding performance. In this paper, the effects of LLR(Log-Likelihood Ratio) approximation on the performance of MSA(Min-Sum Algorithm)-based LDPC decoder are analyzed, and some optimal design conditions are derived. The parity check matrix with block length of 1,944 bits and code rate of 1/2 in IEEE 802.11n WLAN standard is used. In the case of $BER=10^{-3}$, the $E_b/N_o$ difference between LLR bit-widths (6,4) and (7,5) is 0.62 dB, and $E_b/N_o$ difference for iteration cycles 6 and 7 is 0.3 dB. The simulation results show that optimal BER performance can be achieved by LLR bit-width of (7,5) and iteration cycle of 7.