• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.13-20
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• 2005

This paper addresses a new blind channel equalization method using fourth-order cumulants of channel inputs and a three-layer neural network equalizer. The proposed algorithm is robust with respect to the existence of heavy Gaussian noise in a channel and does not require the minimum-phase characteristic of the channel. The transmitted signals at the receiver are over-sampled to ensure the channel described by a full-column rank matrix. It changes a single-input/single-output (SISO) finite-impulse response (FIR) channel to a single-input/multi-output (SIMO) channel. Based on the properties of the fourth-order cumulants of the over-sampled channel inputs, the iterative algorithm is derived to estimate the deconvolution matrix which makes the overall transfer matrix transparent, i.e., it can be reduced to the identity matrix by simple recordering and scaling. By using this estimated deconvolution matrix, which is the inverse of the over-sampled unknown channel, a three-layer neural network equalizer is implemented at the receiver. In simulation studies, the stochastic version of the proposed algorithm is tested with three-ray multi-path channels for on-line operation, and its performance is compared with a method based on conventional second-order statistics. Relatively good results, withe fast convergence speed, are achieved, even when the transmitted symbols are significantly corrupted with Gaussian noise.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1654-1659
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• 2003

In this paper, the performance evaluation of the JADE-MUSIC estimation based on the indoor channel is presented. By means of the JADE-MUSIC algorithm, DOA and time delay can be obtained simultaneously. In the JADE-MUSIC method, the channel impulse response is first estimated from the received samples and then this impulse response is employed to estimate DOAs and time delays of multipath waves. Moreover, according to the JADE-MUSIC characteristics, it can work in cases when the number of impinging waves is more than the number of antenna elements, unlike the traditional parametric subspace-based method, such a case is not true. Therefore, we employ the JADE-MUSIC algorithm applying for the real indoor environment where is rich of the multipath propagation waves and can imply that the number of waves is very possibly higher than that of the array element. The experiment is carried out in our laboratory considered to be the real indoor environment. The performance of the JADE-MUSIC algorithm is evaluated in terms of the comparison between the simulation and experiment results by using the simulated channel model and the real indoor channel model, respectively. It is clear that the joint angle and delay estimation using the simulated channel model are in good agreement with the estimation using the real indoor channel model. Therefore, we can say that the JADE-MUSIC algorithm accomplishes the high performance to jointly estimate the angle and delay of the arriving signal for the indoor environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4967-4986
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• 2015

Multi-hop relaying communications have great potentials in improving transmission performance by deploying relay nodes. The benefit is critically dependent on the accuracy of the channel state information (CSI) of all the transmitting links. However, the CSI has to be estimated. In this paper, we investigate the channel estimation problem in one-way multi-hop MIMO amplify-and-forward (AF) relay system, where both the two-hop and three-hop communication link exist. Traditional point-to-point MIMO channel estimation methods will result in error propagation in estimating relay links, and separately tackling the channel estimation issue of each link will lose the gain as part of channel matrices involved in multiple communication links. In order to exploit all the available gains, we develop a novel channel estimation model by structuring different communication links using the PARAFAC and PARATUCK2 tensor analysis. Furthermore, a two-stage fitting algorithm is derived to estimate all the channel matrices involved in the communication process. In particular, essential uniqueness is further discussed. Simulation results demonstrate the advantage and effectiveness of the proposed channel estimator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2A
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• pp.43-50
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• 2005

In this paper, we present an improved channel estimation method for orthogonal frequency division multipexing systems using pilot symbol assisted modulation(PSAM). Conventional linear minimum mean square error(LMMSE) channel estimation method uses only pilot symbols for channel estimation. So, as the fading channel varies rapidly, the system performance is degraded. The basic idea of the proposed scheme is that we firstly estimate channel coefficients at the middle point between two pilot symbols and then compute the channel attenuation by using LMMSE method. Superior performance achieved with the proposed method is illustrated by simulation experiments with the Doppler frequency of 36Hz and 185Hz in comparison with conventional LMMSE channel estimator.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.3
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• pp.80-84
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• 2014

Dark channel prior means that, for undistorted outdoor images, at least one color channel of a pixel or its neighbors have values close to 0, and thus the prior can be used to estimate the amount of distortion for given distorted images. In other words, if an image is distorted by blur, its dark channel values are averaged with neighbor pixel values and thus increase. This paper proposes a method that estimates blur strengths by analyzing the variation of dark channel values caused by blur. Through experiments with images distorted by Gaussian and horizontal motion blur with given strengths, the usefulness of the proposed method is verified.

• Journal of Distribution Research
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• v.1 no.1
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• pp.83-107
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• 1996

The concern of external environment is growing up in the field of channel distribution. In the former channel distribution, the channel distribution environment is little bit unmoveable owing to a powerful manufacture control against poor distributor. Therefore intra-efficiency is channel member's core interest. The structure of channel governance, however, come to be changable because of the mature distributor power against manufacturer such as a Price Break, JIT of channel governance, and a serial of change. Accordingly, it is acceptable that the interest of external-environment of channel members' is more and more enlarged, and external-environment change in the channel distribution make the serious problems in intraorganizational system. Thus, it is meaningful that this study try to discover the consumer power as external environment factor and to find the best strategy to overcome this consumer power. Resource dependence theory, Transaction cost theory, Political Economic Approach, and Working partnership Approach are the theory foundation of the reasearch. Apparel franchise is a sample to analyse the hypothesis and correlation and multi-regression are a chief tools to estimate the hypothesis. Thus, the above results imply that a flexible governance is appropriate to consumer power, conflict is not intervening value between consumer power and channel governance, and the channel member's satisfaction can be confirmed in the flexible governance better than control governance.

• The Journal of the Acoustical Society of Korea
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• v.26 no.8
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• pp.426-431
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• 2007

In this paper we have studied the underwater vector channel modeling for MIMO(Multiple Input Multiple Output) to increase the performance and efficiency for ultrasound communication in underwater channel environments. Also we have analyzed the MIMO techniques using the proposed channel modeling. For underwater MIMO channel modeling. experiments were done in real channel environments and the data were analyzed to estimate parameters such as fading, Doppler, time delay, angle of arrival, and receiving power. These were used for modeling of underwater vector channel modeling for MIMO. Additionally, we have analyzed the performance of MIMO systems using our proposed channel models. As a result we could see that the BER has decreased severely with the same SNR when using the MIMO system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.252-256
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• 2011

We analyze the channel capacity with considering the effect of the loading conditions of indoor PLC networks on channel state information. We consider various numbers of load for two kinds of the networks with regular length branches and a deployed network of indoor PLC. For calculating the channel capacity degradation, two noise scenarios and impedances are considered. From the simulation results, we suggest the robust regression lines for modeling the channel capacity degradation. In the cases of 0 $\Omega$ and $Z_0$ loads, natural log and linear function curve show the best goodness of fit, respectively. For the deployed indoor PLC network with 0 $\Omega$ loads, compared with the networks with regular length branches, the goodness of fit decreases by the amount of 0.12 and 0.15 for low noise and high noise scenarios, respectively. Using the regression lines, we can estimate the channel capacity degradation without measurement.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.268-271
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• 2014

Conventional forward error correction (FEC) code rate decision schemes using analytical source coding distortion model and channel-induced distortion model are usually complex, and require the typical process of model parameter training which involves potentially high computational complexity and implementation cost. To avoid the complex modeling procedure, we propose a simple but accurate joint source-channel distortion model to estimate channel loss threshold set for optimal FEC code rate decision.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1689-1699
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• 2006

A nonlinear channel blind equalizer by using a hybrid genetic algorithm, which merges a genetic algorithm with simulated annealing, and a RBF network is presented. In this study, a hybrid genetic algorithm is used to estimate the output states of a nonlinear channel, based on the Bayesian likelihood fitness function, instead of the channel parameters. From these estimated output states, the desired channel states of the nonlinear channel are derived and placed at the center of a RBF equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a conventional genetic algorithm(GA) and a simplex GA, and the relatively high accuracy and fast convergence of the method are achieved.