• International journal of advanced smart convergence
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• v.10 no.1
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• pp.75-81
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• 2021

As the number of connected smart devices and applications increases explosively, the existing orthogonal multiple access (OMA) techniques have become insufficient to accommodate mobile traffic, such as artificial intelligence (AI) and the internet of things (IoT). Fortunately, non-orthogonal multiple access (NOMA) in the fifth generation (5G) mobile networks has been regarded as a promising solution, owing to increased spectral efficiency and massive connectivity. In this paper, we investigate the achievable data rate for non-orthogonal multiple access (NOMA) with negatively-correlated information sources (CIS). For this, based on the linear transformation of independent random variables (RV), we derive the closed-form expressions for the achievable data rates of NOMA with negatively-CIS. Then it is shown that the achievable data rate of the negatively-CIS NOMA increases for the stronger channel user, whereas the achievable data rate of the negatively-CIS NOMA decreases for the weaker channel user, compared to that of the positively-CIS NOMA for the stronger or weaker channel users, respectively. We also show that the sum rate of the negatively-CIS NOMA is larger than that of the positively-CIS NOMA. As a result, the negatively-CIS could be more efficient than the positively-CIS, when we transmit CIS over 5G NOMA networks.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.9-12
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• 1991

The correlation search method yields velocity information by tracking scatter patterns between medical image frames. The displacement vector between a target region and the best correlated search region indicates the magnitude and direction of the inter-frame motion of that particular region. However, if the noise sources in the target region and the search region are correlated Gaussian, then the cross-correlation technique fails to work well because it estimates the cross-correlation of both signals and noises. In this paper we develop a new correlation search method which seeks the best correlated third-order statistics between a target and the search region to suppress the effect of correlated Gaussian noise sources. Our new method yields better estimations of velocity than the conventional cross-correlation method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3557-3571
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• 2014

We develop a secret key generation scheme using phase estimation in ultra-wideband (UWB) wireless fading channels. Based on the reciprocity theorem, two terminals extract the phase of the channel as a common random source to generate secret bits. Moreover, we study the secret key rate by a pair of nodes observing correlated sources and communicating to achieve secret key agreement over public communication channels. As our main results, we establish a more practical upper bound from Cramer-Rao bound (CRB) and compare it with a universally theoretical upper bound on the shared maximum key rate from mutual information of correlated random sources. Derivation and numerical examples are presented to demonstrate the bound. Simulation studies are also provided to validate feasibility and efficiency of the proposed scheme.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.304-306
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• 2001

Various methods for blind source separation (BSS) are based on independent component analysis (ICA) which can be viewed as a nonlinear extension of principal component analysis (PCA). Most existing ICA methods require certain nonlinear functions, the shapes of which depend on the probability distributions of sources (which is not known in advance), whereas FCA is a linear learning method based on only second-order statistics. In this paper we show how BSS can be achieved by FCA, provided that sources are spatially uncorrelated but temporally correlated.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.285-293
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• 2021

This study aims to identify the relationship between outcome expectancy and illegal use of music sources, and examined the parallel double mediating model of reward sensitivity and social dilution of responsibility on that relationship. To achieve the purpose this study, data were collected from 302 male and female high school students living in Seoul metropolitan area, and a double mediating effect was analysed with PROCESS Macro 3.5 Model 4. Results indicated that outcome expectancy was positively correlated with reward sensitivity, social dilution of responsibility, and illegal use of music sources of high school students, whereas reward sensitivity and social dilution of responsibility were positively correlated with illegal use of music sources. This study found that reward sensitivity and social dilution of responsibility were mediating outcome expectancy and illegal use of music sources in parallel. These findings suggest that psychological mechanisms lead adolescents use illegal music sources might be important, and provide useful information for making strategies to prevent adolescents' uses of illegal music sources.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.651-658
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• 2020

In the fifth generation (5G) mobile networks, the interactive mobile game users have increased tremendously, which induces correlated information sources (CIS). One of the promising 5G technologies is non-orthogonal multiple access (NOMA). In NOMA, the users share the channel resources, so that CIS affect each user's bit-error rate (BER) performance, which is not the case for orthogonal multiple access (OMA). In this paper, we derive the optimal receiver for NOMA with CIS, and then investigate the impact of CIS on each user's BER performance.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.42-51
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• 2020

In this paper, the authors propose the pseudo complex correlation coefficient (PCCC) of the two complex random variables (RV), because the four real correlation coefficients (RCC) of the corresponding four real RVs cannot be obtained only from the complex correlation coefficient (CCC) of given two complex RV. Such observation is motivated by the general statement; "The complex jointly-Gaussian random M-vector cannot be completely described by the complex covariance matrix, even though the real Gaussian random 2M-vector can be completely descried by the real covariance matrix. Therefore, in order to describe completely the complex jointly-Gaussian random M-vector, we need an additional matrix, namely the complex pseudo-covariance matrix, along with the complex covariance matrix." Then, we apply PCCC to correlated information sources (CIS) for non-orthogonal multiple access (NOMA) in 5G system, and investigate impact of the proposed PCCC on the achievable data rate of the stronger channel user in the conventional successive interference cancellation (SIC) NOMA with CIS. It is shown that for the given same CCC, the achievable data rates with the different PCCC are different, because the corresponding RCC are different. We also show that as the absolute value of the same CCC increases, the impact of the different PCCC becomes more significant.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.457-464
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• 2021

This paper investigates the achievable rate volumes for non-successive interference cancellation(SIC) non-orthogonal multiple access(NOMA) schemes, especially for 3-user correlated information sources(CIS). First, the closed-form expressions for the achievable rate volumes of non-SIC 3-user CIS NOMA are derived. Then it is numerically shown that the large correlation coefficients, as the achievable rate volumes of non-SIC 3-user CIS NOMA is larger than that of conventional SIC 3-user independent information sources(IIS) NOMA. We also demonstrate by various comparisons that the impact of the correlation coefficients of weaker channel gain users on achievable rate volume is more significant than those of stronger channel gain users.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.59-64
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• 2005

To achieve a goal of minimum output power, the beamformer tends to cancel the desired signal if there exists correlated interference sources such as multipaths of the desired signal. In this paper, we propose a new method which overcomes the signal cancellation problem for correlated interferences. Instead of decorrelating the correlated interferences, the proposed bramformer regards them as replicas of the desired signal and coherently combines them with desired signal. This method uses an eigenvector constraint that suppresses a noise and uncorrelated interferences but keeps the desired signal and correlated interferences. Indisputably, the beamformer does not require any preliminary information on correlated interferences. Simulation results show that the proposed beamformer overcomes the signal cancellation problem and improves signal-to-noise ratio (SNR) of the array output when the correlated interferences exist.

• Asian-Australasian Journal of Animal Sciences
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• v.4 no.4
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• pp.305-328
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• 1991

Pig breeding programs have been very successful in the improvement of animals by the simple expedient of focusing on a few traits of economic importance, particularly growth efficiency and leanness. Further reductions in leanness may become more difficult to achieve, due to reduced genetic variation, and less desirable, due to adverse correlated effects on meat and eating quality. Best linear unbiased prediction (BLUP) of breeding values makes possible the incorporation of data from many sources and increases the value of including traits such as sow performance in the breeding objective. Advances in technology, such as electronic animal identification, electronic feeders, improved ultrasonic scanners and automated data capture at slaughter houses, increase the number of sources of information that can be included in breeding value predictions. Breeding program structures will evolve to reflect these changes and a common structure is likely to be several or many breeding farms genetically linked by A.i., with data collected on a number of traits from many sources and integrated into a single breeding value prediction using BLUP. Future developments will include the production of a porcine gene map which may make it possible to identify genes controlling economically valuable traits, such as those for litter size in the Meishan, and introgress them into nucleus populations. Genes identified from the gene map or from other sources will provide insight into the genetic basis of performance and may provide the raw material from which transgenic programs will channel additional genetic variance into nucleus populations undergoing selection.