• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.317-320
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• 2001

Blind adaptive channel identification of communication channels is a problem of important current theoretical and practical concerns. Recently proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling leading to the so-called, second order statistics techniques. And adaptive blind channel identification techniques based on a off-line least-squares approach have been proposed. In this paper, a new approach is proposed that is based on eigenvalue decomposition. And the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the received signals contains the channel impulse response. And we present a adaptive algorithm to solve this problem. The performance of the proposed technique is evaluated over real measured channel and is compared to existing algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.39-49
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• 2015

Some characters and construction theorems of Pseudo Jacket Matrix which is generalized from Jacket Matrix introduced by Jacket Matrices: Construction and Its Application for Fast Cooperative Wireless signal Processing[27] was announced. In this paper, we proposed some examples of Pseudo inverse Jacket matrix, such as $2{\times}4$, $3{\times}6$ non-square matrix for the MIMO channel. Furthermore we derived MIMO singular value decomposition (SVD) pseudo inverse channel and developed application to utilize SVD based on channel estimation of partitioned antenna arrays. This can be also used in MIMO channel and eigen value decomposition (EVD).

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.2 s.332
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• pp.23-38
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• 2005

The state of channel between two or more wireless terminals is changed frequently due to noise or multiple environmental conditions in wireless network. In this paper, we analyze packet transmission time and queue length in a time-varying channel of packet based Wireless Networks. To reflect the feature of the time-varying channel, we model the channel as two-state Markov model and three-state Markov model Which are transformed to SFG(Signal Flow Graph) model, and then the distribution of the packet transmission can be modeled as Gaussian distribution. If the packet is arrived with Poisson distribution, then the packet transmission system is modeled as M/G/1. The average transmission time and the average queue length are analyzed in the time-varying channel, and are verified with some simulations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.59-68
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• 2017

Random process plays a major role in wireless communication system to analytically derive the probability distribution function of the various statistical distribution. In this paper, we derive the decreasing function of the exponential distribution under the given condition which is expressed as wireless channel condition. The probability distribution function of Gaussian, Laplacian, Rayleigh and Nakagami distribution are also derived. Extensive simulation results of these statistical distributions are provided to prove that random process has a significant role in the wireless communications. In addition, the Rayleigh and Rician channels show specific examples of visible distance communication and invisible distance channel environment. This paper is motivated by that we assume a block fading channel model, where the channel is constant during a transmission block and changes independently between consecutive transmission block, can achieve a better performance in high SNR regime with i.i.d channel. This algorithm for realizing these transforms can be applied to the Kronecker MIMO channel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2457-2464
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• 2015

Distributed Networked Control Systems (NCSs) through wireless networks have a tremendous potential to improve the efficiency of various control systems. In this paper, we define the State Update Interval (SUI) as the elapsed time between successful state vector reports derived from the NCSs. A simple expression of the SUI is derived to characterize the key interactions between the control and communication layers. This performance measure is used to formulate a novel optimization problem where the objective function is the probability to meet the SUI constraint and the decision parameter is the channel access probability. We prove the existence and uniqueness of the optimal channel access probability of the optimization problem. Furthermore, the optimal channel access probability for NCSs is lower than the channel access probability to maximize the throughput. Numerical results indicate that the improvement of the success probability to meet the SUI constraint using the optimal channel access probability increases as the number of nodes increases with respect to that using the channel access probability to maximize the throughput.

• The Journal of the Acoustical Society of Korea
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• v.38 no.2
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• pp.207-213
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• 2019

In this paper, we evaluate the communication performance of convolutional code with block interleaving in a frequency-selective channel. Block interleaving is a technique for spreading and rearranging digital data streams. A block interleaving technique is applied to improve the performance by dispersing the concentration of burst errors in a frequency-selective channel. As a result of evaluating the performance of the convolutional code with block interleaving in the water tank experiment, There was no difference in the performance of convolutional codes using block interleaving in a frequency-selective channel. However, in the frequency-selective channel, the convolutional code with block interleaving has a gain of 2dB, and it is confirmed that the underwater acoustic communication performance is improved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1397-1404
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• 2015

Recently, high data rate transmission is required in maritime communication. In this paper, we consider multiple input multiple output (MIMO) spatial multiplexing (SM). However, the performance of SM is severly degraded due to spatial channel correlation and line-of-sight (LOS) component. In the maritime communication, the MIMO channel correlation and LOS are critical due to the lack of scatteres around the transmitter and/or the receiver. When the feedback of channel information is available, precoding can enhance the error performance by exploiting the channel information. However, it is difficult to derive closed-form solution considering both the correlation and LOS. In this paper, we present open-loop precoding-based spatial multiplexing transmission method by showing that the effect of performance for the correlation and LOS. It is shown that the open-loop precoding can mitigate the performance degradation due to the LOS as well as the correlation. Consequently, we expect that the proposed open-loop precoding can be adopted to the maritime communication system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.1
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• pp.9-15
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• 2011

Communication environments in the context of underwater channel are characterized to be bad by the characteristics of multipath. Multipaths are affected by various factors e.g. the temperature and the salinity of the ocean. In this paper, the representative sound speed profiles were calculated in the southern part of Baengnyeoung island so that the eigen-ray paths with the channel impulse responses were determined using the average sound speed profile of last decade. The performance of underwater communication was analyzed using the BPSK modulation and time reversal method. The significant differences of results were shown according to the change of season and carrier frequency by using computer simulation. In addition, improved performance is obtained using preprocess channel impulse response for the better comparison of two cases of summer and autumn.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.58-67
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• 2020

In this paper, we propose a data-driven-based beam selection scheme for massive multiple-input and multiple-output (MIMO) systems in ultra-dense networks (UDN), which is capable of addressing the problem of high computational cost of conventional coordinated beamforming approaches. We consider highly dense small-cell scenarios with more small cells than mobile stations, in the millimetre-wave band. The analog beam selection for hybrid beamforming is a key issue in realizing millimetre-wave UDN MIMO systems. To reduce the computation complexity for the analog beam selection, in this paper, two deep neural network models are used. The channel samples, channel gains, and radio frequency beamforming vectors between the access points and mobile stations are collected at the central/cloud unit that is connected to all the small-cell access points, and are used to train the networks. The proposed machine-learning-based scheme provides an approach for the effective implementation of massive MIMO system in UDN environment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.7
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• pp.641-648
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• 2002

The study on the chip waveform design to minimize multiple-access interference (MAI) and its performance evaluation are very important since chip waveform decides the signal quality and system capacity of the direct-sequence CDMA wireless communication system. This paper suggests the analytical chip waveform to minimize the MAI. The BER and throughput performances achieved by the proposed analytical optimum chip waveform are compared with those of the conventional chip waveforms in the Nakagami-m distribution frequency selective channel when the differential phase shift keying (DPSK) is employed in DS-CDMA system. From the numerical results, capacity and throughput are improved about 2 times and 1.4 times respectively when it is compared with the Kaiser chip waveform that is considered as one of the best in the conventional ones.