• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2052-2055
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• 2003

본 논문은 MDC의 전송 중 발생한 에러를 검출하고, 그 에러를 정정하는 알고리즘을 제안한다. 이 알고리즘은 기존의 MDC 와 같이 약간의 redundancy를 가지는 두 개의 sub-bitstream 을 생성하는데, 한쪽 sub-bitstream에 에러가 발생하였을 때, 다른 한쪽의 sub-bitstream을 이용하여, 발생한 비트 에러를 정정한다. 제안된 알고리즘에 대한 BER-SNR실험은 Generalized Gaussian source를 임의적으로 발생시켜서 결과를 얻어내었다. sub-bitstream에서 에러가 발생하였을 때 우리가 제안한 알고리즘은 BER<10/sup -3/에서 기존 알고리즘보다 약 12㏈ 높은 성능을 얻을 수 있었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1125-1132
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• 2004

In this Paper, we Propose an effective boundary matching based error detection algorithm using causal neighbor blocks to improve video quality degraded from channel error in block-coded video. The proposed algorithm first calculates boundary mismatch powers between a current block and each of its causal neighbor blocks. It then decides that a current block should be normal if all the mismatch powers are less than an adaptive threshold, which is adaptively determined using the statistics of the two adjacent blocks. In some experiments under the environment of 16bi1s burst error at bit error rates (BERs) of 10$^{-3}$ -10$^{-4}$ , it is shown that the proposed algorithm yields the improvements of maximum 20% in error detection rate and of maximum 3.5㏈ in PSNR of concealed kames, compared with Zeng's error detection algorithm.

• Journal of IKEEE
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• v.10 no.1 s.18
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• pp.69-74
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• 2006

In this paper, we present symbol detection methods for decision feedback equalizers (DFE) in trellis coded modulation systems. The proposed symbol detectors improve symbol error rate (SER) by exploiting the coding structure of trellis coded modulation (TCM). For example, for 8-PAM signals the achieved SER with the proposed detection scheme is improved to $2{\times}10^{-5}$ from $2.5{\times}10^{-2}$ of the conventional symbol-by-symbol detector under AWGN channel at 20dB SNR. This SER improvements mitigate error propagation of DFE.and produces significant over-all SER improvement for under multipath channels (for example, from 0.26 to 0.01 and 0.005 under a severe multipath channel 20dB SNR as shown in the simulation result of this paper).

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.3
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• pp.185-197
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• 2001

Recently, the design method by VHDL coding and synthesis has been used widely. As the integration ratio increases, the amount design by VHDL at a time also increases so many coding errors occur in a design. Thus, lots of time and effort is dissipated to detect those coding errors. This paper proposed a method to verify the coding errors in VHDL behavioral-level designs. As the methodology, we chose the method to detect the coding error by applying the generated set of verifying patterns and comparing the responses from the error-free case(gold unit) and the real design. Thus, we proposed an algorithm to generate the verifying pattern set for the coding errors. Verifying pattern generation is peformed for each code and the coding errors are classified as two kind: condition errors and assignment errors. To generate the patterns, VHDL design is first converted into the corresponding CDFG(Control & Data Flow Graph) and the necessary information is extracted by searching the paths in CDFG. Path searching method consists of forward searching and backward searching from the site where it is assumed that coding error occurred. The proposed algorithm was implemented with C-language. We have applied the proposed algorithm to several example VHDL behavioral-level designs. From the results, all the patterns for all the considered coding errors in each design could be generated and all the coding errors were detectable. For the time to generate the verifying patterns, all the considered designed took less than 1 ［sec］ of CPU time in Pentium-II 400MHz environments. Consequently, the verification method proposed in this paper is expected to reduce the time and effort to verify the VHDL behavioral-level designs very much.

• ETRI Journal
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• v.45 no.2
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• pp.213-225
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• 2023

Physical layer security (PLS) can improve the security of both terrestrial and nonterrestrial wireless communication networks. This study proposes a simplified framework for nonterrestrial cyclic prefixed orthogonal variable spreading factor (OVSF)-encoded multiple-input and multiple-output nonorthogonal multiple access (NOMA) systems to ensure complete network security. Various useful methods are implemented, where both improved sine map and multiple parameter-weighted-type fractional Fourier transform encryption schemes are combined to investigate the effects of hybrid PLS. In addition, OVSF coding with power domain NOMA for multi-user interference reduction and peak-toaverage power ratio (PAPR) reduction is introduced. The performance of $\frac{1}{2}$-rated convolutional, turbo, and repeat and accumulate channel coding with regularized zero-forcing signal detection for forward error correction and improved bit error rate (BER) are also investigated. Simulation results ratify the pertinence of the proposed system in terms of PLS and BER performance improvement with reasonable PAPR.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.93-113
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• 2020

According to information theory, non-orthogonal transmission can achieve the multiple-user channel capacity with an onion-peeling like successive interference cancellation (SIC) based detection followed by a capacity approaching channel code. However, in multiple antenna system, due to the unideal characteristic of the SIC detector, the residual interference propagated to the next detection stage will significantly degrade the detection performance of spatial data layers. To overcome this problem, we proposed a modified power-domain non-orthogonal multiple access (P-NOMA) scheme joint designed with space-time coding for multiple input multiple output (MIMO) NOMA system. First, with proper power allocation for each user, inter-user signals can be separated from each other for NOMA detection. Second, a well-designed quasi-orthogonal space-time block code (QO-STBC) was employed to facilitate the SIC-based MIMO detection of spatial data layers within each user. Last, we proposed an optimization algorithm to assign channel coding rates to balance the bit error rate (BER) performance of those spatial data layers for each user. Link-level performance simulation results demonstrate that the proposed time-space-power domain joint transmission scheme performs better than the traditional P-NOMA scheme. Furthermore, the proposed algorithm is of low complexity and easy to implement.

• Journal of Communications and Networks
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• v.6 no.1
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• pp.9-18
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• 2004

Self-encoded multiple access (SEMA) is a unique realization of random spread spectrum. As the term implies, the spreading code is obtained from the random digital information source instead of the traditional pseudo noise (PN) code generators. The time-varying random codes can provide additional security in wireless communications. Multi-rate transmissions or multi-level grade of services are also easily implementable in SEMA. In this paper, we analyze the performance of SEMA in additive white Gaussian noise (AWGN) channels and Rayleigh fading channels. Differential encoding eliminates the BER effect of error propagations due to receiver detection errors. The performance of SEMA approaches the random spread spectrum discussed in literature at high signal to noise ratios. For performance improvement, we employ multiuser detection and Turbo coding. We consider a downlink synchronous system such as base station to mobile communication though the analysis can be extended to uplink communications.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.243-247
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• 2005

We propose an efficient block least-mean-square (BLMS) adaptive algorithm, in conjunction with error control coding, for direct-sequence code division multiple access (DS-CDMA) systems. The proposed adaptive receiver incorporates decision feedback detection and channel encoding in order to improve the performance of the standard LMS algorithm in convolutionally coded systems. The BLMS algorithm involves two modes of operation: (i) The training mode where an uncoded training sequence is used for initial filter tap-weights adaptation, and (ii) the decision-directed where the filter weights are adapted, using the BLMS algorithm, after decoding/encoding operation. It is shown that the proposed adaptive receiver structure is able to compensate for the signal-to­noise ratio (SNR) loss incurred due to the switching from uncoded training mode to coded decision-directed mode. Our results show that by using the proposed adaptive receiver (with decision feed­back block adaptation) one can achieve a much better performance than both the coded LMS with no decision feedback employed. The convergence behavior of the proposed BLMS receiver is simulated and compared to the standard LMS with and without channel coding. We also examine the steady-state bit-error rate (BER) performance of the proposed adaptive BLMS and standard LMS, both with convolutional coding, where we show that the former is more superior than the latter especially at large SNRs ($SNR\;\geq\;9\;dB$).

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.7-10
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• 1998

The error performance of 16 Square-QAM signal with Optimum Threshold Detection(OTD) under the consideration of AWGN and Rician fading was analyzed for various value of Rician fading depth K. And error performance of 16-QAM signal with OTD, which considered in AWGN and Rician fading, was compared with that of 16-QAM signal with OTD, which considered in Rician fading only. And BCH coding is adopted. From the results, the error perfomance evlauated by proposed OTD was superior to that of 16-QAM signal with OTD, which considered in Rician fading without AWGN, in low CNR.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1306-1313
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• 2018

The randomness and incipient nature of certain faults in reactor systems warrant a robust and dynamic detection mechanism. Existing models and methods for fault diagnosis using different mathematical/statistical inferences lack incipient and novel faults detection capability. To this end, we propose a fault diagnosis method that utilizes the flexibility of data-driven Support Vector Machine (SVM) for component-level fault diagnosis. The technique integrates separately-built, separately-trained, specialized SVM modules capable of component-level fault diagnosis into a coherent intelligent system, with each SVM module monitoring sub-units of the reactor coolant system. To evaluate the model, marginal faults selected from the failure mode and effect analysis (FMEA) are simulated in the steam generator and pressure boundary of the Chinese CNP300 PWR (Qinshan I NPP) reactor coolant system, using a best-estimate thermal-hydraulic code, RELAP5/SCDAP Mod4.0. Multiclass SVM model is trained with component level parameters that represent the steady state and selected faults in the components. For optimization purposes, we considered and compared the performances of different multiclass models in MATLAB, using different coding matrices, as well as different kernel functions on the representative data derived from the simulation of Qinshan I NPP. An optimum predictive model - the Error Correcting Output Code (ECOC) with TenaryComplete coding matrix - was obtained from experiments, and utilized to diagnose the incipient faults. Some of the important diagnostic results and heuristic model evaluation methods are presented in this paper.