• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1901-1904
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• 2002

A good performance on communication systems is obtained by decreasing the length of training sequence In the initial stage of adaptive equalization. This paper presents a new approach to accomplish this, with the use of a training adaptive equalizer. The approach is based on combining the training and tracking modes, in which the training equalizer is updated by the LMS algorithm with the training sequence and then updated by a blind algorithm. By computer simulations, it is shown that a class of the proposed equalizers provides better performance than the conventional training equalizer.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3209-3211
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• 1999

We propose a robust Dual-Mode blind equalization algorithm based on Quadrant-partitioned Constant Modulus Algorithm (QCMA) and Modified Constant Modulus Algorithm(MCMA) for QAM demodulation and its performance evaluated. The proposed algorithm show that the stability in setting 2d range and the faster convergence accomplished to conventional Dual-Mode algorithm.

• Journal of Communications and Networks
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• v.12 no.5
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• pp.399-405
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• 2010

Blind equalization techniques have been used in broadcast and multipoint communications. In this paper, two criteria of minimizing Euclidian distance between two probability density functions (PDFs) for adaptive blind equalizers are presented. For PDF calculation, Parzen window estimator is used. One criterion is to use a set of randomly generated desired symbols at the receiver so that PDF of the generated symbols matches that of the transmitted symbols. The second method is to use a set of Dirac delta functions in place of the PDF of the transmitted symbols. From the simulation results, the proposed methods significantly outperform the constant modulus algorithm in multipath channel environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8A
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• pp.760-767
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• 2010

For complex channel blind equalization, this study presents the performance and characteristics of two complex blind information theoretic learning algorithms (ITL) which are based on minimization of Euclidian distance (ED) between probability density functions compared to constant modulus algorithm which is based on mean squared error (MSE) criterion. The complex-valued ED algorithm employing constant modulus error and the complex-valued ED algorithm using a self-generated symbol set are analyzed to have the fact that the cost function of the latter forces the output signal to have correct symbol values and compensate amplitude and phase distortion simultaneously without any phase compensation process. Simulation results through MSE convergence and constellation comparison for severely distorted complex channels show significantly enhanced performance of symbol-point concentration with no phase rotation.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.7
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• pp.65-75
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• 1996

The probability distributio function (pdf) of transmitted symbols should be asymmectric for recovering the received data in the 3rd order blind equalizer system. In this paper, we hav edesigned the blind equalizer using symmetric-asymmetric (SA) and asymmetric-symmetric (AS) transforms for less computational complexities and robustness in the noisy environments. The method of SA and AS transform was peformed using natural logarithmic operation. This paper proves that the proposed in this paper can be performed as real time operation. This paper proves that the compression factor k has no effet on transmitted symbols. Also 3rd order equalization method proposed in this paper can be performed as real time operation. As a result of computer simulatio, the computational complexity of proposed algorithm is reduced to be an half of 4th order method and MSE is enhanced as 10dB at the case of 4-PAM and 15dB at the case of 8-PAM respectivley. Conclusively, we have found that 3rd order blind equalizer can be implemented when the pdf of transmitter is asymmetric.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.69-72
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• 2001

Blind equalization of transmission channel is important in communication areas and signal processing applications because it does not need training sequence, nor does it require a priori channel information. Recently, Tong et al. proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the second order statistics techniques, fur example, subspace method, prediction error method, and so on. The linear prediction error method is perhaps the most attractive in practice due to the insensitive to blind equalizer length mismatch as well as for its simple adaptive filter implementation. Unfortunately, the previous one-step prediction error method is known to be limited in arbitrary delay. In this paper, we induce the optimal delay, and propose the adaptive blind equalizer with multi-step linear prediction using RLS-type algorithm. Simulation results are presented to demonstrate the proposed algorithm and to compare it with existing algorithms.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.4
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• pp.295-299
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• 2011

Blind equalization techniques have been widely used in wireless communication systems. In this paper, we propose to apply the balanced information potentials to the criterion of minimum Euclidian distance between two PDFs with constant modulus errors for adaptive blind equalizers. One of the two PDFs is constructed with constant modulus error samples and another does with Dirac delta functions. Two information potentials derived from the criterion are balanced in order to have better performance by putting a weighting factor to each information potentials. The proposed blind algorithm has shown in the MSE convergence performance that it can produce enhanced performance by over 3 dB of steady state MSE.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.26-32
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• 2013

Blind algorithms based on Information potential of output samples and a set of symbols generated in random order at the receiver go through performance degradation when biased impulsive noise is added to the channel since the cost function composed of information potentials has no variable to deal with biased signal. Aiming at the robustness against biased impulsive noise, we propose, in this paper, a modified information potential, and derived related blind algorithms based on augmented filter structures and a set of random-order symbols. From the simulation results of blind equalization for multipath channels, the blind algorithm based on the proposed information potential produced superior convergence performance in the environments of strong biased impulsive noise.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.87-95
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• 2009

As information theoretic learning techniques, error entropy minimization criterion (MEE) and maximum cross correntropy criterion (MCC) have been studied in depth for supervised learning. MEE criterion leads to maximization of information potential and MCC criterion leads to maximization of cross correlation between output and input random processes. The weighted combination scheme of these two criteria, namely, minimization of Error Entropy with Fiducial points (MEEF) has been introduced and developed by many researchers. As an approach to unsupervised, blind channel equalization, we investigate the possibility of applying constant modulus error (CME) to MEE criterion and some problems of the method. Also we study on the application of CME to MEEF for blind equalization and find out that MEE-CME loses the information of the constant modulus. This leads MEE-CME and MEEF-CME not to converge or to converge slower than other algorithms dependent on the constant modulus.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1777-1786
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• 1996

This paper describes theories and implementation techniques of a digital high-definition television(HDTV) modem based on 32-QAM for terrestrial broadcasting. We proposed a digital demodulation scheme and a symbol timing recovery structure based on the band edge component maximization(BECM) method. The adaptive equalizer has 256 complex taps to remove the multipath of delays ranging from -2.mu.s~+24.mu.s with a new T/2-spaced blind equalization algorithm. computer simulation results reveal that the proposed algorithm outperforms other conventional blind equalization algorithm a digital HDTV modem with 4.91MHz symobol rate is implemented by utilizing the proposed algorithms. All processings for modem operations such as demodulation, estimation of symbol timing phase error, adaptive equalization, and carrier recovery except IF signal processing and sampling phase control part of the AD converter are done in digital domain. Especially, the carrier recovery loop can track a carrier offset of upto .+-.350KHz.