• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.177-186
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• 2005

This paper introduces nonlinear estimators with reduced complexity, and proposes the Bussgang blind equalization algorithm employing the nonlinear estimators. The proposed algorithm utilized the facts that the Bayesian estimator is well approximated to the sigmoid estimator in initial stage of equalization with closed eye and is well approximated to the threshold estimator under open eye condition. The proposed method adopts selectively one of the two nonlinear estimators, i.e., the sigmoid estimator and the threshold estimator, according to channel distortion level at each iteration. As a result, by using the sigmoid estimator with reduced constellation, the proposed scheme, as it is applied to blind equalization of high-order QAM signals, simplifies the computational complexity extremely, and enhances the blind convergence capability and steady-state performance.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2E
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• pp.43-48
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• 2006

Abstract-Using the recursive generalized eigendecomposition method, we develop a recursive form solution to the data least squares (DLS) problem, in which the error is assumed to lie in the data matrix only. Simulations demonstrate that DLS outperforms ordinary least square for certain types of deconvolution problems.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.3-5
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• 2007

This paper presents decision feedback equalizers using a recurrent neural network trained algorithm using extended Kalman filter(EKF) and sigma-point Kalman filter(SPKF). EKF is propagated, analytically through the first-order linearization of the nonlinear system. This can introduce large errors in the true posterior mean and covariance of the Gaussian random variable. The SPKF addresses this problem by using a deterministic sampling approach. The features of the proposed recurrent neural equalizer And we investigate the bit error rate(BER) between EKF and SPKF.

• 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 Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.753-758
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• 2011

The constant modulus algorithm (CMA) widely used in blind equalization applications minimizes the averaged power of constant modulus error (CME) defined as the difference between an instant output power and a constant modulus. In this paper, a decision feedback version of the linear blind algorithm based on maximization of the zero-error probability for CME is proposed. The Gaussian kernel of the maximum zero-error criterion is analyzed to have the property to cut out excessive CMEs that may be induced from severely distorted channel characteristics. Decision feedback approach to the maximum zero-error criterion for CME is developed based on the characteristic that the Gaussian kernel suppresses the outliers and this prevents error propagation to some extent. Compared to the linear algorithm based on maximum zero-error probability for CME in the simulation of blind equalization environments, the proposed decision feedback version has superior performance enhancement particularly in cases of severe channel distortions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5C
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• pp.521-526
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• 2009

In this paper, a complex-valued recursive least squares escalator filter algorithm with reduced computational complexity for complex-valued signal processing applications is presented. The local tap weight of RLS-ESC algorithm is updated by incrementing its old value by an amount equal to the local estimation error times the local gain scalar, and for the gain scalar, the local input autocorrelation is calculated at the previous time. By deriving a new gain scalar that can be calculated by using the current local input autocorrelation, reduced computational complexity is accomplished. Compared with the computational complexity of the complex-valued version of RLS-ESC algorithm, the computational complexity of the proposed method can be reduced by 50% without performance degradation. The reduced computational complexity of the proposed algorithm is even less than that of the LMS-ESC. Simulation results for complex channel equalization in 64QAM modulation schemes demonstrate that the proposed algorithm has superior convergence and constellation performance.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.7
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• pp.47-53
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• 2004

In this paper we introduce a complex escalator (ESC) structure-Equalizer and investigate its performance in complex channels in QPSK undulation systems. The proposed complex equalizer has the complete orthogonalization property and is independent of eigenvalue spread ratio (ESR) of channel. The proposed complex ESC equalizer shows as 7 times faster convergence speed as that of the conventional complex TDL equalizer algorithms in a complex channel model for QPSK systems.

• Journal of Communications and Networks
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• v.14 no.1
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• pp.27-33
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• 2012

In this paper, a new blind signal processing scheme for equalization in fading and impulsive-noise channel environments is introduced based on probability density functionmatching method and a set of Dirac-delta functions. Gaussian kernel of the proposed blind algorithm has the effect of cutting out the outliers on the difference between the desired level values and impulse-infected outputs. And also the proposed algorithm has relatively less sensitivity to channel eigenvalue ratio and has reduced computational complexity compared to the recently introduced correntropy algorithm. According to these characteristics, simulation results show that the proposed blind algorithm produces superior performance in multi-path communication channels corrupted with impulsive noise.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.15-20
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• 2016

The existing multiple modulus-based self-recovering equalization type has not been applied to initial equalization. Instead, it was used for steady-state performance improvement. In this paper, for the self-recovering equalization type that considers the multiple modulus as a desired response, the initial convergence performance was improved by extending the dynamics of the errors using error boosting and their characteristics were analyzed. Error boosting in the proposed method was carried out in proportion to a symbol decision for the equalizer output. Furthermore, having the initial convergence capability by extending the dynamics of errors, it showed excellent performance in the initial convergence rate and steady-state error level. In particular, the proposed method can be applied to the entire process of equalization through a single algorithm; the existing methods of switching over or the selection of other operation modes, such as concurrent operating with other algorithms, are not necessary. The usefulness of the proposed method was verified by simulations performed under the channel conditions with multipath propagation and additional noise, and for performance analysis of self-recovering equalization for high-order signal constellations.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.829-832
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• 2001

본 논문에서는 2차 통계치를 이용하여 패널추징 및 등화 기법을 제안하였다. 기존의 채널 추정 알고리듬은 잡음이 없는 환경에서 LS방법을 이용하기 때문에 잡음이 강한 패널에서는 원하는 성능을 얻을 수 없는 단점이 있다. 수신신호의 상관행렬의 최소 고유값에 대응하는 고유벡터는 채널의 임펄스 응답에 관한 정보를 포함하고 있다. 이러한 고유 벡터를 매시간마다 갱신시키면서 구하는 적응 알고리듬을 제안하고 이를 이용하여 블라인드 채널 추정 및 등화기 파라미터를 추정하였다. 제안한 알고리듬은 잡음에 강인한 특성을 보일 뿐 아니라 기존의 알고리듬들 보다 우수한 채널 추정 및 등화 성능을 모의 실험을 통하여 검증하였다.