• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.299-306
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• 2011

In this paper, a blind adaptive equalization algorithm based on PDF-distance minimization and a set of Delta functions is introduced and its superior robustness against impulsive noise and multipath characteristics of underwater communication channels is proved. The conventional CMA based on MSE has shown to be incapable of coping with impulsive noise, and correntropy blind algorithm has also revealed to yield not satisfying performance for the mission. On the other hand, the blind adaptive equalization algorithm based on PDF-distance minimization and a set of Delta functions has been proved to solve effectively the problem of impulsive noise and multipath characteristics of underwater communication channels through theoretical and simulation analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2451-2458
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• 1997

Adaptive channel equalization complished without resorting to a training sequence is known as blind equalization. In this paper, in order to increase the speed of the convergence and to reduce the steady-state mean squared error simulatneously, we propose the multi-stage DD(decision-direct) algorithm derived from the combination of the Sato algorithm and the decision-directed algorithm. In the starting stage, the multi-stage DD algorithm is identical to the Sato algorithm which guarantees the convergence of the equalizer. As the blind equalizer converges, the number of the level of the quantizers is increased gradally, so that the proposed algorithm operates identical to the decision-directed algorithm which leads to the low error power after the convergence. Therefore, the multi-stage DD algorithm obtains fast convergence rate and low steady state mean squared error.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.5
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• pp.2347-2352
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• 2012

In this paper, a new alternating equalizer and its differential adjustment algorithm are proposed. The proposed alternating equalizer achieves equalization effectively using an algorithm performing symbol decisions based on soft/hard decision. In addition, it is possible to improve the initial blind convergence speed and steady-state error performance simultaneously by adjusting the equalizer differentially according to the relative reliability of the symbol decisions by soft/hard decision devices. The simulation results on 16/64-QAM constellations under multipath propagation channel and additive noise conditions confirmed to support usefulness of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3C
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• pp.157-162
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• 2011

For blind equalization of communication channels, concurrent equalization is useful to improve convergence characteristics. However, the concurrent equalization will result in limited performance enhancement by continuing concurrent adaptation with two algorithms after the equalizer converges to steady-state. In this paper, to improve the convergence characteristics and steady-state performance of the concurrent equalization, proposed is a new concurrent equalization technique with variable step-size parameter and weight-based tap coefficients update. The proposed concurrent vsCMA+DD equalization calculates weight factors using error signals of the variable step-size CMA (vsCMA) and DD (decision-directed) algorithm, and then updates the two equalizers based on the weights respectively. The proposed method, first, improves the error performance of the CMA by the vsCMA, and enhances the steady-state performance as well as the convergence speed further by the weight-based tap coefficients update. The performance improvement by the proposed scheme is verified through simulations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.477-480
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• 2005

CMA-DD is proposed to improve the steady-state performance of CMA and its performance is depending on switching time between two modes of operation. Castro et al. who proposed a concurrent equalizer for solving problem of CMA-DD, which reduced the sensibility of switching time. However, concurrent algorithm has a problem that it keeps working after convergence. In this paper, we propose concurrent MCMA-DD equalizer combined modified CMA(MCMA) and DD mode for making better concurrent algorithm. The proposed equalizer is better than previous algorithm in convergence speed and steady-state performance. Also, the proposed algorithm decides optimum switching time using residual ISI of the equalizer output.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.1957-1967
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• 1997

Adaptive channel equlization accomplished without resorting to a training sequence is known as blind equalization. In this paper, in order to reduce the speed of the convergence and the steady-state mean squared error simultaneously, we propose the multi-stage RD(radius-directed) algorithm derived from the combination of the constant modulus algorithm and the radius-directed algorithm. In the starting stage, multi-stage RD algorithm are identical to the constant modulus algorithm which guarantees the convergence of the equalizer. As the blind identical to the constant modulus algorithm which guarantees the convergence of the equalizer. As the blind equalizer converges, the number of the level of the quantizers is increased gradually, so that the proposed algorithm operate identical to the radius-directed algorithm which leads to the low error power after the covnergence. Therefore, the multi-stage RD algorithm obtains fast convergence rage and low steady stage mean square error.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3660-3665
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• 2012

For blind equalization, it is necessary to open an eye pattern quickly in the early stage of equalization, after that it is important to lower an error level of equalizer output signal. This paper discusses coarse error estimation using signal points specifically determined and fine error estimation using original signal constellation, and proposes two suggestions for how to take advantage of the two error estimation methods. The two error estimates, respectively, are effective to quickly open an eye pattern in the state of eye pattern closed, or to lower the level of an error in the steady-state after the eye pattern opening. Two blind equalization algorithms are proposed and their performances are compared, which select one of the two error estimates depending on the state of convergence of the equalizer, or combine two errors weightedly according to the relative reliabilities of the two error estimates, and calculate the new error.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.3-8
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• 2015

In this paper, we propose a blind equalization algorithm based on the error signal linearly combined a constellation-matched error (CME) and a non-constellation-matched error (non-CME). The new error signal was designed to include the non-CME term for reaching initial convergence and the CME term for improving intersymbol interference (ISI) performance of output signals, and it controls the error terms through a combining factor. By controlling the error terms, it generates an appropriate error signal for equalization process and improves convergence speed and ISI cancellation performance compared to those of conventional algorithms. In the simulation for 64-QAM and 256-QAM signals under the multipath channel and additive noise conditions, the proposed method was superior to CMA and CMA+DD concurrent equalization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.11
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• pp.645-651
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• 2014

For blind equalization, we propose a method of updating an equalizer, which generates an error from selectively applying a transmitted symbol constellation and that of induced equivalently from the transmitted symbol constellation and updates the equalizer by using this error. The proposed method, by selectively using the symbol constellation effective for improvement of symbol estimation accuracy and that of effective for improvement of error performance, showed that it is possible to improve the error performance at the same time to open the eye diagram of equalizer output quickly. As a criterion applying the symbol constellation, we used the dispersion of symbol points of equalizer output. In addition, to increase the accuracy of updating an equalizer the error was controlled by using current and previous dispersions. By simulation, under multipath channel with additive noise, we verified the equalization performance of the proposed method for 64-QAM.