Sooyong Choi

Yonsei University, Sŏul, Seoul, South Korea

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Publications (41)20.57 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: In this letter, asynchronous multicarrier-code division multiple access (MC-CDMA) systems with a cyclic prefix (CP) are analyzed over frequency-selective multipath fading channels, and the average bit error rate is evaluated. The derived results show that a CP is required for MC-CDMA systems in order to mitigate intersymbol interference (ISI) and fully obtain the achievable path diversity as the frequency diversity.
    IEEE Communications Letters 03/2005; · 1.16 Impact Factor
  • Sooyong Choi, Te-Won Lee, Daesik Hong
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    ABSTRACT: An adaptive error-constrained least mean square (AECLMS) algorithm is derived and proposed using adaptive error-constrained optimization techniques. This is accomplished by modifying the cost function of the LMS algorithm using augmented Lagrangian multipliers. Theoretical analyses of the proposed method are presented in detail. The method shows improved performance in terms of convergence speed and misadjustment. This proposed adaptive error-constrained method can easily be applied to and combined with other LMS-type stochastic algorithms. Therefore, we also apply the method to constant modulus criterion for blind method and backpropagation algorithm for multilayer perceptrons. Simulation results show that the proposed method can accelerate the convergence speed by 2 to 20 times depending on the complexity of the problem.
    Signal Processing 01/2005; 85:1875-1897. · 2.24 Impact Factor
  • Sooyong Choi, Te-Won Lee
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    ABSTRACT: In this paper, we introduce and investigate a new adaptive equalization method based on minimizing approximate negentropy of the estimation error for a finite-length equalizer. We consider an approximate negentropy using nonpolynomial expansions of the estimation error as a new performance criterion to improve performance of a linear equalizer based on minimizing minimum mean squared error (MMSE). Negentropy includes higher order statistical information and its minimization provides improved converge, performance and accuracy compared to traditional methods such as MMSE in terms of bit error rate (BER). The proposed negentropy minimization (NEGMIN) equalizer has two kinds of solutions, the MMSE solution and the other one, depending on the ratio of the normalization parameters. The NEGMIN equalizer has best BER performance when the ratio of the normalization parameters is properly adjusted to maximize the output power(variance) of the NEGMIN equalizer. Simulation experiments show that BER performance of the NEGMIN equalizer with the other solution than the MMSE one has similar characteristics to the adaptive minimum bit error rate (AMBER) equalizer. The main advantage of the proposed equalizer is that it needs significantly fewer training symbols than the AMBER equalizer. Furthermore, the proposed equalizer is more robust to nonlinear distortions than the MMSE equalizer.
    IEEE Transactions on Neural Networks 08/2004; 15(4):928-36. · 2.95 Impact Factor
  • Sooyong Choi, Te-Won Lee
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    ABSTRACT: In this paper, we introduce an information theoretic learning method as a new approach to multiuser detection. We propose a new adaptive linear multiuser detector based on approximate negentropy minimization of the output error and investigate its characteristics and performance. Negentropy includes higher order statistical information and its minimization provides improved converge and performance compared to traditional methods such as minimum mean squared error. The proposed algorithm is derived under the assumption that a Gaussian variable has the largest entropy among all random variables of unit variance and hence a normalization process is required. Simulation experiments show that our multiuser detector has similar bit error rate (BER) characteristics to the least BER multiuser detector. Furthermore, the proposed detector has faster convergence speed than the LBER detector.
    Global Telecommunications Conference, 2003. GLOBECOM '03. IEEE; 01/2004
  • Sooyong Choi, Te-Won Lee
    [Show abstract] [Hide abstract]
    ABSTRACT: We introduce and investigate a new adaptive equalization method based on minimizing approximate negentropy of the estimation error for a finite-length equalizer. We consider an approximate negentropy using non-polynomial expansions of the estimation error as a new performance criterion to improve performance of a linear equalizer based on minimizing minimum mean squared error (MMSE). The proposed equalizer, called the NEGMIN equalizer, has two kinds of solutions, the MMSE solution and the other one, depending on the ratio of the normalization parameters. The NEGMIN equalizer has the best bit error rate (BER) performance when the ratio of the normalization parameters is properly adjusted to maximize the output power (variance) of the NEGMIN equalizer. Simulation experiments show that BER performance of the NEGMIN equalizer with the other solution than the MMSE one has similar characteristics to the adaptive minimum BER (AMBER) equalizer. The main advantage is that the proposed equalizer needs significantly fewer training symbols than the AMBER equalizer. Furthermore, the proposed equalizer is much more robust to nonlinear distortions compared to the NMSE equalizer.
    Vehicular Technology Conference, 2003. VTC 2003-Fall. 2003 IEEE 58th; 11/2003
  • Sooyong Choi, Te-Won Lee
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    ABSTRACT: An equalisation method based on negentropy minimisation is introduced and its characteristics are investigated. Negentropy includes higher order statistical information and its error minimisation provides improved convergence and performance. The bit error ratio of the proposed method has similar characteristics to the adaptive minimum bit error rate (AMBER) equaliser. The main advantage of the proposed equaliser is that it needs drastically fewer training iterations than the AMBER and the MMSE equalisers.
    Electronics Letters 05/2003; · 1.04 Impact Factor
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    ABSTRACT: This paper proposes a novel detection scheme using a radial basis function (RBF) network in a multi-input multi-output (MIMO) environment. In order to evaluate the performance of the proposed MIMO-RBF receiver, simulations are performed over the rich-scattering fading channel. Simulation results confirm that the proposed scheme shows the similar bit-error rate (BER) performance of a maximum likelihood detection (MLD) and outperforms Vertical-Bell Laboratories Layered Space-Time using minimum-mean-square-error ing (VBLAST-MMSE) as well as VBLAST using zero-forcing ing (VBLAST-ZF). Moreover, we investigate the effect on the performance of the number of RBF center with two modulation formats (i.e. BPSK and QPSK) and different number of transmit and receive antennas. The performance of the proposed detector is verified with respect to an initialization-rate of RBF centers.
    Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE; 12/2002
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    ABSTRACT: Asynchronous multicarrier-code division multiple access (MC-CDMA) systems employing a cyclic prefix for the uplink in a multipath fading channel are analyzed. The uncoded bit-error rate performance of the system is obtained. Derived analysis and simulation results show that the guard period is required for MC-CDMA systems in order to mitigate intersymbol interference (ISI) and the performance of asynchronous MC-CDMA systems is sensitive to the correlation among the sub-carriers.
    MILCOM 2002. Proceedings; 11/2002
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    ABSTRACT: The authors propose a multiuser detector with channel estimation capability using a radial basis function (RBF) network in a synchronous multicarrier-code division multiple access (MC-CDMA) system. The authors propose to connect an RBF network to the frequency domain to effectively utilize the frequency diversity. Simulations were performed over frequency-selective and multi-path fading channels. These simulations confirmed that the proposed receiver can be used both for the channel estimation and as a multi-user receiver, thus permitting an increase in the number of active users
    IEEE Transactions on Neural Networks 12/2001; · 2.95 Impact Factor
  • Sooyong Choi, Kyunbyoung Ko, Daesik Hong
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    ABSTRACT: In order to reduce the complexity of a single hidden layer multilayer neural network, a new two hidden layer MFNN (THL-MFNN) with a combined structure of a RBFN and MLPs is proposed, and its associated training method is discussed. The proposed THL-MFNN can be easily constructed, and can be efficiently trained by online recursive methods. The performance of the proposed THL-MFNN with P/4+2=18 hidden nodes and 34 weights is equal to that of an optimum Bayesian equalizer using an RBFN with P=64 hidden nodes and 64 weights. The role of each layer in the proposed THL-MFNN is presented by a theoretical approach, and the feasibility of a more reduced structure is given
    Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on; 02/2001
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    ABSTRACT: An accurate analytical method of an asynchronous direct sequence (DS) code division multiple access (CDMA) system using a interference cancellation (IC) technique is proposed. In this analysis, a RAKE receiver is considered over uplink fading channels that are modeled as slowly varying Rayleigh-fading discrete multi-path channels. By Monte Carlo simulations, it is shown that the proposed analysis is more exact to simulation results than the previous ones.
    Military Communications Conference, 2001. MILCOM 2001. Communications for Network-Centric Operations: Creating the Information Force. IEEE; 02/2001
  • Sooyong Choi, Kyunbyoung Ko, Daesik Hong
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    ABSTRACT: In order to accelerate the convergence speed of the conventional BP algorithm, constrained optimization techniques are applied to the BP algorithm. First, the noise-constrained least mean square algorithm and the zero noise-constrained LMS algorithm are applied (designated the NCBP and ZNCBP algorithms, respectively). These methods involve an important assumption: the filter or the receiver in the NCBP algorithm must know the noise variance. By means of extention and generalization of these algorithms, the authors derive an adaptive error-constrained BP algorithm and its simplified algorithm, in which the error variance is estimated. This is achieved by modifying the error function of the conventional BP algorithm using Lagrangian multipliers. The convergence speeds of the proposed algorithms are 20 to 30 times faster than those of the conventional BP algorithm, and are faster than or almost the same as that achieved with a conventional linear adaptive filter using an LMS algorithm
    Neural Networks for Signal Processing XI, 2001. Proceedings of the 2001 IEEE Signal Processing Society Workshop; 02/2001
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    ABSTRACT: We propose a new suboptimal detector that uses orthogonal polynomial approximation to determine the stage weighting factors at each interference cancellation (IC) stage. The performance of the new detector using the proposed scheme is compared with that of other sub-optimal detectors in the near-far and additive white Gaussian noise (AWGN) environments. Simulation results show that the average convergence rate of the proposed method for obtaining the optimum solution through estimation of the minimum (and maximum) eigenvalue of the code correlation matrix is faster than for other sub-optimal detectors based on IC. In addition, the method described here is also able to obtain better BER performance, with the same number of stages, than conventional parallel interference cancellation in the above environments
    Vehicular Technology Conference, 2001. VTC 2001 Fall. IEEE VTS 54th; 02/2001
  • Sooyong Choi, Kyunbyoung Ko, Daesik Hong
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    ABSTRACT: This paper presents nonlinear blind equalization techniques using an adaptive bilinear polynomial filter. Two types of blind adaptive bilinear polynomial equalizers with reduced bilinear terms are proposed. One is a blind bilinear polynomial decision feedback equalizer using conventional constant modulus algorithm, which uses previous detected symbols. The other is a blind predictive constant modulus bilinear decision feedback equalizer, which uses error signals. In proposed equalizers, the input of the bilinear section is composed of the feedback inputs multiplied by not overall but middle parts of feedforward inputs. It can be seen by various simulations that proposed simplified blind bilinear equalizers perform better than the conventional blind decision feedback equalizer (DFE) and has almost the same performance as the conventional DFE using training sequences in a digital communication system
    Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on; 02/2001
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    ABSTRACT: The sub-optimum RBF receiver is proposed to reduce not only the complexity with regard to the number of centers, but also required instructions per one bit reception. By Monte Carlo simulations over the additive white Gaussian noise channel, it is confirmed that the proposed receiver with reduced complexity can be used to obtain the near optimum performance. Moreover, the proposed receiver can properly cope with manifold environment
    Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on; 02/2001
  • Sooyong Choi, Kyunbyoung Ko, Daesik Hong
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    ABSTRACT: In this paper, the adaptive error constrained least mean square (AECLMS) algorithm is proposed through the extension and generalization of the noise constrained LMS (NCLMS) algorithm and its performance analysis is presented. By using a constrained optimization technique, the assumption that the noise variance is known is eliminated. Therefore, the proposed constrained optimization method can be easily applied to blind equalization methods. The proposed constrained method is also applied to the constant modulus criterion. The proposed method can accelerates the convergence speed of the conventional steepest descent-type training procedure by several times
    Global Telecommunications Conference, 2001. GLOBECOM '01. IEEE; 02/2001
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    ABSTRACT: The polynomial perceptron multiuser demodulator (PPMUD) and the bilinear recursive polynomial perceptron multiuser demodulator with decision feedback (BRPMUD) are applied to a digital communication system using spread spectrum. The proposed multiuser demodulators are compared with the conventional receiver, the multilayer perceptron multiuser demodulator (MLPMUD) and the radial basis function multiuser demodulator (RBFMUD) in terms of bit-error rate (BER). In order to obtain a satisfactory BER, the structure of the PPMUD is complex and needs long training periods. On the other hand, the BRPMUD shows good performance and has a much simpler structure than the other multiuser demodulators using neural networks
    Neural Networks for Signal Processing X, 2000. Proceedings of the 2000 IEEE Signal Processing Society Workshop; 02/2000
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    ABSTRACT: The performance of an MC-CDMA system with carrier frequency offsets in correlated multipath fading is mathematically analyzed. The bit error rate is obtained from such analysis for the uplink Rayleigh fading channel. The derived results show that the performance of the MC-CDMA system is sensitive to the frequency offset, and the correlation of the subcarriers. That is, the performance degradation of the MC-CDMA system is caused by both carrier frequency offset and correlation among subcarriers. From the derived results, however, the performance degradation due to correlation among subcarriers is more severe than effect of frequency offset
    Communications, 2000. ICC 2000. 2000 IEEE International Conference on; 02/2000
  • Sooyong Choi, Daesik Hong
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    ABSTRACT: In order to improve the performance and simplify the structure of an equalizer using a bilinear recursive polynomial perceptron (BRPE), a new equalizer, which is an equalizer using a bilinear recursive polynomial perceptron with decision feedback (BRPDFE), is proposed. The proposed BRPDFE is compared with the BRPE in terms of mean square error (MSE). The performance is compared with the conventional decision feedback equalizer (DFE), the multilayer perceptron decision feedback equalizer (MRPDFE) and the BRPE in terms of bit-error rate (BER) in true data transmission systems. They ar compared on a digital communication system in which the dominant distortion factor is intersymbol interference and a digital storage system in which the primary interference element is nonlinear distortion. The results from analysis and simulation show that the proposed BRPDFE is superior to the other equalizers. Moreover, the BRPDFE has the simpler structure than the other equalizers
    Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on; 02/2000
  • Kyunbyoung Ko, Sooyong Choi, Daesik Hong
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    ABSTRACT: A multi-user detector with an ability of channel estimation using a radial basis function (RBF) network is proposed in a multicarrier-code division multiple access (MC-CDMA) system. In the proposed scheme, the RBF network is connected to the frequency domain to effectively utilize the frequency diversity. Simulations were performed over the frequency selective and multipath fading channel. From these simulations, the proposed receiver is verified to be used for both the channel estimation and the multi-user receiver that permits more active users
    Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on; 02/2000

Publication Stats

202 Citations
20.57 Total Impact Points

Institutions

  • 1997–2005
    • Yonsei University
      • Department of Electrical and Electronic Engineering
      Sŏul, Seoul, South Korea
  • 2004
    • National University (California)
      San Diego, California, United States
    • CSU Mentor
      Long Beach, California, United States
  • 1998
    • Dongguk University
      • Division of Electronics and Electrical Engineering
      Seoul, Seoul, South Korea