• Journal of Navigation and Port Research
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• v.37 no.3
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• pp.269-273
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• 2013

Underwater acoustic channels are generally recognized as one of the most difficult communication media because of the multipath propagation, dispersion, and so on. MIMO (Multiple-input multiple-output) techniques have been actively pursued in underwater acoustic communications recently to increase the data rate over the bandwidth-limited channels. The transmit diversity techniques can be applied in this case, and one of them is Alamouti's scheme. In this paper the performances of the transmit diversity technique are evaluated via experiment. Two transmitters and two receivers were used in experiment, and the experiment was performed in indoor water tank. The error rate 5~8% was confirmed in experimental results, and these are the improved values than the error rate 14.8% for SISO(Single-input single-output) channel under same data rate condition.

• Korean Management Science Review
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• v.15 no.2
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• pp.125-142
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• 1998

The aggregation on linear large-scale dynamic systems is examined in this paper and a "two-step" approach is proposed. In this procedure, the aggregated system consists of two subsystems. The first subsystem represents aggregation through the retainment of dominant eigenvalues of the original system, leading to a first approximation of the desired output of the original system. The purpose of augmenting it with a second subsystem is to provide an estimation of the error on the first approximation, thus permitting a second correction to the output approximation and resulting in an output approximation of greater accuracy. Optimization techniques are discussed for the determination of unknown parameters in the aggregated system. These techniques use minimization principles of certain suitable performance indices and are developed for both single input-single output and multiple input-multiple output system. Numerical examples illustrating these procedures are given and the results are compared with those obtained using existing methods. Finally, a pharmacokinetics problem is studied from the aggregation point of view.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.79-84
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• 2017

This paper is a multi-input multi-path (Multiple-input multiple-output: MIMO) using a space-alternating generalized expectation maximization(SAGE) algorithm in the parameter channel and determine the channel estimation performance. Estimated by the algorithm, SAGE time-varying channel environment, the channel parameters estimated from the parameters of the channel measured in the island region 781 of the band in order to compare the performance and compares the original data. This allows you to check the performance of the algorithm SAGE and is highly stable to delay spread (Delay Spread), the diffusion angle of arrival (Arrive of Angular Spread) performance in terms of accuracy down through the SAGE algorithm for estimating a more general calculation parameters.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.634-646
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• 2015

Assuming perfect channel state information (CSI) at the transmitter and receiver, the optimization problem of maximizing the minimum Euclidean distance between two received signals by a linear precoder is considered for multiple-input multiple-output (MIMO) systems with arbitrary dimensions and arbitraryary quadrature amplitude modulation (QAM) input. A general precoding framework is first presented based on the Gram matrix, which is shown for 2-dimensional (2-D) and 3-dimensional (3-D) MIMO systems when employing the ellipse expanding method (EEM). An extended precoder for high-dimensional MIMO system is proposed following the precoding framework, where the Gram matrix for high-dimensional precoding matrix can be generated through those chosen from 2-D and 3-D results in association with a permutation matrix. A complexity-reduced maximum likelihood detector is also obtained according to the special structure of the proposed precoder. The analytical and numerical results indicate that the proposed precoder outperforms the other precoding schemes in terms of both minimum distance and bit error rate (BER).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3458-3478
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• 2022

Automatic modulation recognition is the core algorithm in the field of modulation classification in communication systems. Our investigations show that deep learning (DL) based modulation recognition techniques have achieved effective progress for multiple-input multiple-output (MIMO) systems. However, network complexity is always an additional burden for high-accuracy classifications, which makes it impractical. Therefore, in this paper, we propose a low-complexity dimensional interactive lightweight network (DilNet) for MIMO systems. Specifically, the signals received by different antennas are cooperatively input into the network, and the network calculation amount is reduced through the depth-wise separable convolution. A two-dimensional interactive attention (TDIA) module is designed to extract interactive information of different dimensions, and improve the effectiveness of the cooperation features. In addition, the TDIA module ensures low complexity through compressing the convolution dimension, and the computational burden after inserting TDIA is also acceptable. Finally, the network is trained with a penalized statistical entropy loss function. Simulation results show that compared to existing modulation recognition methods, the proposed DilNet dramatically reduces the model complexity. The dimensional interactive lightweight network trained by penalized statistical entropy also performs better for recognition accuracy in MIMO systems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.188-197
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• 2012

DEA 모델중 널리 사용되는 교차평가모델(cross efficiency model)은 가중치에 제한을 두지 않고 어떤 특정분야에 탁월한 성과를 내는 DMU(Decision Making Unit)보다는 보다 전반적인 분야에서 두각을 나타내는 DMU를 선발함으로써 많은 연구자들이 DEA문헌에서 적용하여 왔다. 본 연구에서는 이러한 교차평가모델이 실제에 있어서는 암묵적으로 고정 가중치를 사용한다는 것과 동일한 결과를 나타낸다는 것을 분석적으로 밝혔다(one input, multi output case). 또한 multi-input, multi-output case의 경우에도 overall performer의 cluster에 근접한 대다수 DMU의 경우에는 고정 가중치를 사용한 경우와 거의 차이가 없음을 보였다. 교차평가 모델에 적용된 변수의 가중치를 보다 명확히 함으로써 연구자들이 모델의 평가결과를 이해하는데 도움이 될 수 있을 것이다. 또한 교차 평가의 가중치 도식을 더 명확히 보여주기 위해 biplot을 제안한다.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.592-594
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• 1998

In the single-input and single-output system, the parameter of plant is scalar polynomial, but in the multiple input and multiple output, it accompanies, being matrix polynomial, the consideration of observable conrolability index or problems of non-commutation in matrix polynomial as well as degree, and it is more complex to deal with. Therefore, it is thought that a full reserach on the single-input and single-output system is not made. This reserach propose that problems of minimum variance self-tuning regulator of multivariable system and pole placement self-tuning regulator.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.481-482
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• 2007

This paper demonstrates OFDM with adaptive modulation applied to Multiple-Input Multiple-Output (MIMO) systems. We apply an optimization algorithm to obtain a bit and power allocation for each subcarrier assuming instantaneous channel knowledge. The analysis and simulation is considered in two stages. The first stage involves the application of a variable-rate variable-power MQAM technique for a Single-Input Single-Output(SISO) OFDM system. This is compared with the performance of fixed OFDM transmission where a constant rate is applied to each subcarrier. The second stage applies adaptive modulation to a general MIMO system by making use of the Singular Value Decomposition to separate the MIMO channel into parallel subchannels. For a two-input antenna, two-output antenna system, the performance is compared with the performance of a system using selection diversity at the transmitter and maximal ratio combining at the receiver.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2298-2304
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• 2015

In this paper, we provide a new approach which optimizes the vertical tilting angle of the base station for multi-cell multiple-input single-output (MISO) downlink active antenna systems (AAS). Instead of the conventional optimal algorithm which requires an exhaustive search, we propose simple and near optimal algorithms. First, we represent a large system approximation based vertical beamforming algorithm which is applied to the average sum rate by using the random matrix theory. Next, we suggest a signal-to-leakage-and-noise ratio (SLNR) based vertical beamforming algorithm which simplifies the optimization problem considerably. In the simulation results, we demonstrate that the performance of the proposed algorithms is near close to the exhaustive search algorithm with substantially reduced complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2614-2632
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• 2015

A multiple symbol detection (MSD) algorithm is proposed relying on soft information for ultra-wideband systems, where differential space-time block code is employed. The proposed algorithm aims to calculate a posteriori probabilities (APP) of information symbols, where a forward and backward message passing mechanism is implemented based on the BCJR algorithm. Specifically, an MSD metric is analyzed and performed for serving the APP model. Furthermore, an autocorrelation sampling is employed to exploit signals dependencies among different symbols, where the observation window slides one symbol each time. With the aid of the bidirectional message passing mechanism and the proposed sampling approach, the proposed MSD algorithm achieves a better detection performance as compared with the existing MSD. In addition, when the proposed MSD is exploited in conjunction with channel decoding, an iterative soft-input soft-output MSD approach is obtained. Finally, simulations demonstrate that the proposed approaches improve detection performance significantly.