• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2405-2411
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• 2009

MMSE, ZF and ML are the decoding mechanisms for V-BLAST system, and ML shows the best performance decoding the original signal among them. However, it has a problem that the computation complexity is increased exponentially according to the number of transmit antennas and transmit degrees. In this paper, we propose a low complexity linear ML detection algorithm having low computation complexity, then analyze the system performance in BER and computation complexity comparing with other algorithms. In the simulation, the BER performance of the proposed algorithm is superior than ZF and MMSE detection algorithms, and similar to ML detection algorithm. However, its computation complexity was 50% less than ML algorithm. From the results, we confirm that the proposed algorithm is superior than other ML detection algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12C
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• pp.1082-1087
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• 2008

Maximum Likelihood (ML) detection is well known to exhibit better bit-error-rate (BER) than many other detectors for multiple-input multiple-output (MIMO) channel. However, ML detection has been shown a difficult problem due to its NP-hard problem. It means that there is no known algorithm which can find the optimal solution in polynomial-time. In this paper, Semi-Definite relaxation (SDR) is iteratively applied to ML detection problem. The probability distribution can be obtained by survival eigenvector out of the dominant eigenvalue term of the optimal solution. The probability distribution which is yielded by SDR is recurred to the received signal. Our approach can reach to nearly ML performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.634-641
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• 2009

The goal of OSIC-series detection methods is to approach the ML performance with feasible complexity. However, since they sometimes suffer from the empty vector problem, they can not achieve the soft-output ML performance or many candidate vectors are required to achieve the soft-output ML performance. In this paper, we propose the novel detection method, which can generate the reliable soft-outputs without suffering from empty vector problem. The proposed detector can approach the near soft-output ML performance as well as hard-output. Further, the complexity study shows that the proposed detection method has the lowest complexity compared to the other detectors having the near ML performance.

• Journal of Animal Science and Technology
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• v.46 no.5
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• pp.841-848
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• 2004

Rapid detection of viable Salmonella in pasteurized milk is important to protect public health from food poisoning. Reverse transcriptase-polymerase chain reaction(RT-PCR) is recognized as a molecular genetical method to differentiate between live and dead bacteria The RT-PCR in this study was designed to detect specifically viable Salmonella in milk by using the primers whose nucleotide sequences were determined based on fimA gene which encodes the submit of type 1 fimbriae. Treatment of RNA preparation with RNase-free DNase was adequate enough to destroy DNA, which may otherwise be amplified in the RT PCR Seven strains of Salmonella were detected in the RT-PCR but Escherichia coli, Shigella sonnei, Citrobacter freundii, and Klebsiella pneumoniae were not. $10^7/ml$ and $10^6/ml$ of dead Salmonella which were heat-treated in milk were detectable by using the RT-PCR but $10^5{\sim}10/ml$ of the dead bacteria were not. The sensitivity of the RT-PCR in detecting viable Salmonella was 100 cells/ml.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.731-738
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• 2017

In this paper, we proposed a modified ML detector for generalized spatial modulation which is a method among Multiple-input Multiple-output. This proposed method detects signal applying modified channel statement information based on priority. Complexity in conventional methods increases as increasing the number of active antennas. To solve this problem, we proposed a new ML method using static channel information decided by the number of transmit antennas and the number of receive antennas. This method detects active antennas one by one through priority. The proposed method has proved benefit on complexity compared with conventional method through simulations. When the number of transmit antennas is equal to 10, there is approximately 45% complexity reduction.

• Research in Plant Disease
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• v.18 no.2
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• pp.73-79
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• 2012

Phytophthora katsurae is a fungal pathogen responsible for chestnut ink disease. We designed two duplex primer sets (SOPC 1F/1R+KatI 3F/5R, SOPC 1-1F/1-1R+KatI 3F/5R) to detect P. katsurae. SOPC 1F/1R and SOPC 1-1F/1-1R primer pairs were designed for sequence characteristic amplification regions (SCAR) marker, and KatI 3F/5R primer pair was used for P. katsurae-specific primer designed from internal transcribed spacer (ITS) region. To assess the sensitivity of duplex PCR, genomic DNA was serially diluted 10-fold to make the final concentrations from 1 mg/ml to 1 ng/ml. The sensitivity for two primer sets were 1 ${\mu}g/ml$ and 100 ng/ml, respectively. To find detection limits for zoospores of P. katsurae, each zoospore suspension was serially diluted 10-fold to make the final concentrations from $1{\times}10^6$ to $1{\times}10^2$ cells/ml, and then DNA was extracted. The limits of detection for all of two primer sets were $1{\times}10^5$ cells/ml. All of two primer sets were specific to P. katsurae in PCR detection and did not produce any P. katsurae-specific PCR amplicons from other 16 Phytophthora species used as the control. This study shows that duplex PCR using two primer sets might be a useful tool for rapid and efficient detection of P. katsurae.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1339-1345
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• 2007

An important drawback in Lattice Reduction (LR) aided detectors has been investigated. For the solution, an improved LR aided detection with ignorable complexity overhead is proposed for MIMO system, where the additional correction operation is performed for the case of unreliable symbol decision. We found that LR aided detection errors mainly occur when the lattice points after the inverse lattice transform in the final step fall outside the constellation point set. In the proposed scheme, we check whether or not the lattice point obtained through LR detection is out of constellation. Only for the case of out of constellation, we additionally perform ML search with reduced search region restricted to the neighboring points near to the obtained lattice points. Using this approach, we can effectively and significantly improve the detection performance with just a slight complexity overhead which is negligible compared to full searched ML scheme. Simulation results show that the proposed scheme achieves the detection performance near to that of the ML detection with a lower computational complexity.

• Journal of Advanced Navigation Technology
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• v.15 no.3
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• pp.392-404
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• 2011

In this paper, we address the issue of joint detection schemes for uplink cellular system when base station cooperation is possible for multi-user detection in multi-cell scenario. The ZF, ML, MMSE and SIC detection are analyzed and evaluated as a conventional scheme. ML attains the optimal performance but the complexity increases exponentially, ZF/MMSE have simple structure but have poor detection performance and SIC has better performance but it has large complexity and potential of the error propagation. However, they need the increased decoder complexity as the number of iteration is increased. We propose a new joint ML and ZF/MMSE detection scheme, which combines the partial ML decoding and ZF/MMSE detection, in order to decrease the decoder complexity. Simulation results show that the proposed scheme attains same or a little bit better BER performance and expect reduced decoder complexity, specially in the case of large number of Base Station are cooperated each other.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9C
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• pp.882-888
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• 2006

Multiuser detection can significantly increase system capacity and improve service quality compared with the existing matched filter. In this paper, we introduce an method which efficiently calculates the maximum likelihood (ML) metric based on the gradient search (GS). The ML detection needs user powers as well as their spreading codes. A method is also proposed that allows us to detect data bits with the estimation of user powers when they are unknown. Computer simulation shows that the proposed method can nearly achieve the same performance as the GS with perfectly hewn user powers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.562-567
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• 2002

Noise predictive maximum likelihood(NPML) detector embeds noise predictions/ whitening process in branch metric calculation of Viterbi detector and improves the reliability of branch metric computation. Therefore, PRML detector with a noise predictor achieves some performance improvement and has an advantage of low complexity. This paper shows that NP(1221)ML system through noise predictive PR-equalized signal has less complexity and better performance than high order PR(12321)ML system in high density perpendicular magnetic recording. The simulation results are evaluated using (1) random sequence and (2) run length limited (1,7) sequence, and they are applied to linear channel and nonlinear channel with normalized linear density $1.0{\leq}K_p{\leq}3.0$.