• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.52-58
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• 2013

This paper proposes an adaptive algorithm based on a method of dynamic error signal generation suitable for signal state by examining the equalizer output signal in blind equalization. In the proposed method, it estimates the error signals using single modulus and multiple modulus each effective to the early stage of equalization or steady-state, and it generates a new error signal from the two error estimates. Two equalizer structures are implemented and their performances are compared: 1-equalizer structure that generates a new error signal by combining the two error estimates weightedly and updates the equalizer using this, and 2-equalizer structure that updates two equalizers respectively depending on the weights of the two error signals. In the proposed method, as the error signals were generated optimally before and after the initial convergence respectively, it was confirmed by computer simulations that the equalizer was updated effectively.

• 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.

• 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.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.4
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• pp.318-324
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• 2013

For blind channel equalization, the reliability of signal estimate determines the convergence speed and steady-state performance of the equalizer. Therefore the nonlinear estimator and reference signal being used in signal estimate should be chosen appropriately. In this paper, to increase the reliability of the signal estimate, two errors were obtained by applying coarse signal points and dense signal points respectively to signal estimate, the relative reliabilities of two errors were calculated, then the equalizer was adapted deferentially utilizing the reliabilities. At this point, by applying two errors alternately, two modes of operation were smoothly combined. Through computer simulations the proposed method was confirmed to achieve fast transient state convergence and low steady-state error compared to traditional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4B
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• pp.237-244
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• 2003

This paper presents the design of a QPSK/16-QAM downstreams receiver chip. The proposed chip consists of a blind equalizer, a timing recovery block and a carrier recovery block. The blind equalizer uses a DFE sturucture using CMA(Constant Module Algorithm). The symbol timing recovery uses the modified parabolic interpolator. The decision-directed carrier recovery is used to remove the carrier frequency offset, phase offset and phase jitter. The implemented LMDS receiver can support four data rates, 10, 20, 30 and 40 Mbps and can accommodate the symbol rate up to 10 Mbaud. This symbol rate is faster than existing QAM receivers.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.54-63
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• 1996

We propose a 3rd order blind equalizer that incorporates a new transform method using either square root operation ($\sqrt{x]$) or reciprocal operation (1/x) in order to transform symmetric distribution of PAM signals at the transmitter, to asymmetric one. At the receiver, either the square operation or the reciprocal operation is needed to recover the asymmetrically transformed signals to the original ones after eualization. The reslts of the computer simulation, using the new method are better than the existing transform method using natural logarithm operation by the maximum of 8 dB in MSE. In addition, as the skewness of the asymmetrically transformed distribution has small values, the performances are improved.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.3-10
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• 2013

Please In this paper, to cope with biased impulsive noise problems, a new information potential is proposed that can move the transmitted symbol points by modifying the information potential designed with Dirac-delta functions. Based on the proposed information potential a new blind algorithm is derived by employing an augmented filter structure. From the simulation results in the environment of biased impulsive noise, the conventional algorithms yield performance degradation by over 15 dB, but the proposed algorithm shows no performance degradation and holds the same steady state MSE of below -25 dB as after the initial convergence regardless of the channel conditions.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.3
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• pp.169-180
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• 2013

The modification of conditional Fuzzy C-Means (CFCM) with Gaussian weights (CFCM_GW) is accomplished for blind equalization of channels in this paper. The proposed CFCM_GW can deal with both of linear and nonlinear channels, because it searches for the optimal desired states of an unknown channel in a direct manner, which is not dependent on the type of channel structure. In the search procedure of CFCM_GW, the Bayesian likelihood fitness function, the Gaussian weighted partition matrix and the conditional constraint are exploited. Especially, in contrast to the common Euclidean distance in conventional Fuzzy C-Means(FCM), the Gaussian weighted partition matrix and the conditional constraint in the proposed CFCM_GW make it more robust to the heavy noise communication environment. The selected channel states by CFCM_GW are always close to the optimal set of a channel even when the additive white Gaussian noise (AWGN) is heavily corrupted. These given channel states are utilized as the input of the Bayesian equalizer to reconstruct transmitted symbols. The simulation studies demonstrate that the performance of the proposed method is relatively superior to those of the existing conventional FCM based approaches in terms of accuracy and speed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6A
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• pp.473-479
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• 2012

In this paper, blind equalization technique using Gaussian two-cluster model is proposed. The proposed approach, by modeling the received M-QAM signals as Gaussian distributed two-cluster, minimizes the computational complexity and enhances the reliability of the signal estimates. In addition, by using a nonlinear estimator with variable parameters to estimate the transmitted signal, and by selectively applying the reduced constellation and the original constellation when estimating the signals, the reliability of the signal estimation was further improved. As a result, the proposed approach has improved the performance while reducing the complexity of the equalizer. Through computer simulations for blind equalization of higher-order signals of 64-QAM, it was confirmed that the proposed method showed better performance than traditional approaches.