• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.25-42
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• 2007

A direct solver for the Legendre tau approximation for the two-dimensional Poisson problem is proposed. Using the factorization of symmetric eigenvalue problem, the algorithm overcomes the weak points of the Schur decomposition and the conventional diagonalization techniques for the Legendre tau approximation. The convergence of the method is proved and numerical results are presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12A
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• pp.1006-1013
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• 2009

This paper proposes a data stream allocation technique for fair capacity performance in multiuser multiple-input multiple-output (MIMO) systems using block diagonalization (BD) algorithm. Conventional studies have been focused on maximum sum capacity. Thus, there is a very large difference of capacity among users, since user capacity unfairly distributed according to each user channel environment. In additional, poor channel user has very small capacity, since base station allocates the power by using water-filling technique. Also, almost studies limited itself to obtain the additional gain by using the same number of data streams for all users. In this paper, we propose the technique for maximizing sum capacity under the fair performance constraint by allocating data stream according to user channel environment. Also, proposed algorithm has more gain of sum capacity and transmit power than conventional equal allocation via computer simulation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.8
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• pp.15-26
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• 2011

In this paper, we present a new beamforming scheme for a downlink of multiuser multiple-input multipleoutput (MIMO) communication systems. Recently, a block-diagonalization (BD) algorithm has been proposed for the multiuser MIMO downlink where both a base station and each user have multiple antennas. However, the BD algorithm is not efficient when the number of supported streams per user is smaller than that of receive antennas. Since the BD method utilizes the space based on the channel matrix without considering the receive combining, the degree of freedom for beamforming cannot be fully exploited at the transmitter. In this paper, we optimize the receive beamforming vector under a zero forcing (ZF) constraint, where all inter-user interference is driven to zero. We propose an efficient algorithm to find the optimum receive vector by an iterative procedure. The proposed algorithm requires two phase values feedforward information for the receive combining vector. Also, we present another algorithm which needs only one phase value by using a decomposition of the complex general unitary matrix. Simulation results show that the proposed beamforming scheme outperforms the conventional BD algorithm in terms of error probability and obtains the diversity enhancement by utilizing the degree of freedom at the base station.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11A
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• pp.1027-1037
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• 2010

In this paper, we propose the linear interpolation-based BD (Block Diagonalization) precoding approximation algorithm for low complexity in downlink multiuser MIMO-OFDM (Multiple-input Multiple-output Orthogonal Frequency Division Multiplexing) systems. In the case of applying the general BD precoding algorithm to multiuser MIMO-OFDM systems, the computational complexity increases in proportional to the number of subcarriers. The proposed interpolation-based BD precoding approximation algorithm can be achieved similar SER performance with general BD algorithm and can decrease the computational complexity. It is proved that proposed algorithm can achieve the significantly decreased computational complexity by computer simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1156-1173
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• 2021

In this paper, we propose a new joint precoder and postcoder design strategy to support multiple streams per user in multiuser multiple-input multiple-output (MIMO) systems. We propose two step precoding strategies using equal channel gain decomposition and block diagonalization at the transmitter. With the proposed precoder, the multiuser MIMO channel can be decomposed into multiple parallel channels with equal channel gain per user. After applying receive postcoder which is generated and sent by the transmitter, we can use ML based decoder per stream to achieve full receive diversity. Achievable sum rate bound and diversity performance of the proposed algorithm are presented with feedback signaling design and quantitative complexity analysis. Simulation results show that the proposed algorithm asymptotically approaches to the sum rate capacity of the MIMO broadcast channel while maintaining full diversity order.

• ETRI Journal
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• v.35 no.2
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• pp.193-199
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• 2013

This paper addresses nonnegative independent component analysis (NICA), with the aim to realize the blind separation of nonnegative well-grounded independent source signals, which arises in many practical applications but is hardly ever explored. Recently, Bertrand and Moonen presented a multiplicative NICA (M-NICA) algorithm using multiplicative update and subspace projection. Based on the principle of the mutual correlation minimization, we propose another novel cost function to evaluate the diagonalization level of the correlation matrix, and apply the multiplicative exponentiated gradient (EG) descent update to it to maintain nonnegativity. An efficient approach referred to as the EG-NICA algorithm is derived and its validity is confirmed by numerous simulations conducted on different types of source signals. Results show that the separation performance of the proposed EG-NICA algorithm is superior to that of the previous M-NICA algorithm, with a better unmixing accuracy. In addition, its convergence speed is adjustable by an appropriate user-defined learning rate.

• Journal of Satellite, Information and Communications
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• v.6 no.1
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• pp.19-27
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• 2011

In this paper, we propose the data stream allocation algorithms for maximizing sum capacity of downlink multiuser MIMO (Multiple-input Multiple-output) systems with BD (Block Diagonalization). The conventional BD precoding algorithms maximize the capacity by controlling power against channel gain of each user. In multiuser MIMO systems, however, the number of data streams for each user can be used to as another control parameter, which determines the capacity. This paper proposes the data stream allocation algorithm of BD for increasing capacity in multiuser MIMO systems. The proposed algorithm allocates unequal bit stream to each user based on channel matrix of each user for maximizing sum capacity. It is proved that proposed algorithm can achieve the significantly improved sum capacity by computer simulation.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.77-90
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• 2002

Network expansion has been an inevitable method for most traffic equilibrium assignments to consider intersection movements such as intersection delays. The drawback of network expansion is that because it dramatically increases network sizes to emulate possible directional movements as corresponding links, not only is complexities for building network amplified, but computational performance is shrunk. This paper Proposes a new variational inequality formulation for a user-optimal traffic equilibrium assignment model to explicitly consider directional delays without building expanded network structures. In the formulation, directional delay functions are directly embedded into the objective function, thus any modification of networks is not required. By applying a vine-based shortest Path algorithm into the diagonalization algorithm to solve the problem, it is additionally demonstrated that various loop-related movements such as U-Turn, P-Turn, etc., which are frequently witnessed near urban intersections, can also be imitated by blocking some turning movements of intersections. The proposed formulation expects to augment computational performance through reduction of network-building complexities.

• The Journal of the Acoustical Society of Korea
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• v.38 no.2
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• pp.177-183
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• 2019

In this paper, we proposed an application method of ICA (Independent Component Analysis) to passive line array sonar to separate interferences from target signals in low frequency band and compared performance of three conventional ICA algorithms. Since the low frequency signals are received through larger bearing angles than other frequency bands, neighboring beam signals can be used to perform ICA as measurement signals of the ICA. We use three ICA algorithms such as Fast ICA, NNMF (Non-negative Matrix Factorization) and JADE (Joint Approximation Diagonalization of Eigen-matrices). Through experiments on real data obtained from passive line array sonar, it is verified that the interference can be separable from target signals by the suggested method and the JADE algorithm shows the best separation performance among the three algorithms.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.553-556
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• 2000

This paper proposes an adaptive linearization method of Volterra nonlinear systems using DWT(Discrete Wavelet Transform)and an LMS-type predistorter. In particular, the proposed wavelet transform-domain lineatization method leads to diagonalization of the input vector auto-correlation matrix which yields improvement of the convergence rate of the corresponding transform-domain LMS algorithm. Furthermore, the adaptive Volterra predistorter followed by a corresponding weakly Volterra nonlinear system(here. a TWT amplifier model in a satellite communication system) is utilized to compensate for the distortion in the output. Also,12-PSK and 4-QAM are applied as the input to the nonlinear system to be tested. Some simulation results show that the proposed linearization approach has better performance than DCT-based or conventional normalized LMS algorithms do.