• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2247-2253
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• 2010

WiBro(Wireless Broadband Internet) is the standard of high-speed portable internet based on OFDMA/TDD (Orthogonal frequency division multiple access / Time division duplexing) techniques, and the subset of consolidated version of IEEE802.16e Wireless MAN standard. In this paper, we propose performance improvements of WiBro system using the LVQ(Learning Vector Quantization) blind equalization. Proposed method used the prefiltering LVQ neural network blind equalization in the Broadband WiBro system receiver. The prefiltering LVQ neural network constellates 16QAM that is transmitter data shape and the blind equalization removes ICI(Inter Carrier Interference). To verificate the proposed method usability, the MSE(Mean Square Error) and the BER(Bit Error Rate) are simulated. The simulation results shown that is improved the performances of the proposed WiBro system using the LVQ blind equalization than the existing WiBro system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.343-347
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• 2012

Non-linear equalization techniques using decision feedback structure are highly demanded for cancellation of intersymbol interferences occurred in severe channel environments. In this paper decision feedback structure is applied to the linear blind equalizer algorithm that is based on information theoretic learning and a randomly generated symbol set. At the decision feedback equalizer (DFE) the random symbols are generated to have the same probability density function (PDF) as that of the transmitted symbols. By minimizing difference between the PDF of blind DFE output and that of randomly generated symbols, the proposed DFE algorithm produces equalized output signal. From the simulation results, the proposed method has shown enhanced convergence and error performance compared to its linear counterpart.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.996-1007
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• 1996

In this paper, a blind adaptation method for a decision feedback equalizer (DFE) is proposed to deal with nominimum phase channels. This equalizer is composed of a linear transversal filter and a prediction error filter which are trained separately using constant modulus and decision feedback prediction algorithms, respectively, during the learnign time. The proposed algorithm guaranetees the DFE to converge to a suboptimal point on the condition that a linear transversal of the proposed scheme is illustrated and the performance is compared with conventional blind equlization algorithms.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.1
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• pp.35-47
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• 2002

This paper proposes a self organizing RBF neural network equalizer for the equalization of digital communications. It is the most important for the equalizer using the RBF neural network to estimate the RBF centers correctly and quickly, which are the desired channel states. However, the previous RBF equalizers are not used in the actual communication system because of some drawbacks that the number of channel states has to be known in advance and many centers are necessary. Self organizing neural network equalizer proposed in this paper can implement the equalization without prior information regarding the number of channel states because it selects RBF centers among the signals that are transmitted to the equalizer by the new addition and removal criteria. Furthermore, the proposed equalizer has a merit that is able to make a equalization with fewer centers than those of prior one by the course of the training using LMS and clustering algorithm. In the linear, nonlinear and standard telephone channel, the proposed equalizer is compared with the optimal Bayesian equalizer for the BER performance, the symbol decision boundary and the number of centers. As a result of the comparison, we can confirm that the proposed equalizer has almost similar performance with the Bavesian enualizer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1638-1645
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• 2008

WiBro(Wireless Broadband Internet) is the standard of high-speed portable internet based on OFDMA/TDD techniques, and the subset of consolidated version of IEEE802.16e Wireless MAN standard. In this paper, we propose the design method of WiBro system using the SOFM Blind Equalization. Proposed design method used SOFM neural network blind equalization with Bussgang algorithms in the Broadband 16 QAM WiBro system receiver. To verificate the proposed design method usability, the MSE and the BER are simulated. The simulation results shown that is improved the equalization performances of the proposed WiBro system using the SOFM Blind equalization than the existing WiBro system.

• Journal of IKEEE
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• v.10 no.1 s.18
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• pp.62-68
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• 2006

In this paper, we propose an adaptation strategy for blind equalizers, which combines a blind algorithm based on high order statistics and the decision directed LMS algorithm. In contrast to 'Stop-and-Go' algorithm, where adaptation is stopped for unreliable signals, the proposed algorithm applies high order statistics (HOS) blind algorithm to the unreliable signals and applies DD-LMS for the reliable signals. The proposed algorithm, named 'Run-and-Go' algorithm, inherits minimum MSE performance of DD-LMS and acquisition ability of blind algorithms. Furthermore, by updating the reliable signal region according to signal quality in each iteration, the convergence speed and acquisition ability is further improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1125-1132
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• 2010

WiBro(Wireless Broadband Internet) is the standard of high-speed portable internet based on OFDMA/TDD (Orthogonal frequency division multiple access / Time division duplexing) techniques, and the subset of consolidated version of IEEE802.16e Wireless MAN standard. In this paper, we propose performance improvements of WiBro system using the 64QAM SOFM(Self-Organizing Feature Maps)prefiltering. Proposed method used the prefiltering SOFM neural network blind equalization in the Broadband 64 QAM WiBro system receiver. The prefiltering SOFM neural network constellates 64QAM that is transmitter data shape and the blind equalization removes ICI(Inter Carrier Interference). To verificate the proposed method usability, the MSE and the BER are simulated. The simulation results shown that is improved the performances of the proposed WiBro system using the 64QAM SOFM Prefiltering than the existing WiBro system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.8 s.350
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• pp.69-76
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• 2006

In this paper, we propose blind adaptation strategies for decision feedback equalizer (DFE) optimizing the operation mode between acquisitionand tracking modes based on adjustable soft decision devices. The proposed schemes select an optimal soft decision device to generate feedback samples for the DFE at a given noise to signal ratio, and apply corresponding adaptation rules which combine a blind infinite impulse response (IIR) filtering adaptation and the decision-directed least mean squared (DD-LMS) DFE adaptation. These adaptation approaches attempt to achieve not only smooth transition between acquisition and tracking of DFE but also mitigation of error propagation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9C
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• pp.1235-1243
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• 2004

In this paper, a new blind equalizer algorithm is proposed which operates on dual mode and combines the benefits of both the Sign-Godard algorithm and the radius-directed algorithm The proposed algorithm has both the properties of good initial convergence of the Sign-Godard algorithm and low residual errors after convergence of the radius-directed algorith High order statistics are used for blind phase recovery and gor avoiding local minima. Simulation results show that the new algorithm has not only faster convergence rated but also lower residual errors than those of the conventional algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6A
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• pp.920-930
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• 1999

Many researches on the multi-level QAM(Quadrature Amplitude Modulation) which is known to be a promising digital data transmission method for efficient use of channel bandwidth have been carried on, and their applications to various real fields are now being in progress. However, in the band-limited communication systems, each transmitted symbols is distorted by the ISI(Intersymbol Interference) and the phase error. Therefore, an equalizer and a carrier recovery must be taken into considerations to attenuate the effects of these distortions in the receiver. This paper presents an effective receiver structures that is applicable to the multi-level QAM. The proposed receiver system is consisted of an equalizer with Godard’s blind algorithm and a carrier recovery circuit. The phase error is estimated with a $\theta$-matching algorithm and is used in the carrier recovery to recover the correct phase. The simulation results are included to evaluate performance of the proposed receiver system for the various channel models.