• Journal of IKEEE
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• v.15 no.4
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• pp.293-298
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• 2011

In the paper, we propose a new CMF(Constant Modulus Fourth) algorithm for WCDMA(Wideband Code Multiple Access) RF(Radio Frequency) Repeater. CMF algorithm is proposed by modifying the CMA(Constant Modulus Algorithm) algorithm and improved performances are achieved by properly adjusting step size values. The steady state MSE(Mean Square Error) performance of the proposed CMF algorithm with step size of 0.35 is about 4dB better than that of the conventional CMA algorithm. And the proposed CMF algorithm requires 400~1100 less iterations than the LMS(Least Mean Square) and NLMS(Normalized Least Mean Square) algorithms at MSE of -25dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.85-90
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• 2009

In this paper, as an alternative to constant modulus algorithm based on MSE, maximization of the probability that equalizer output power is equal to the constant modulus of the transmitted symbols is introduced. The proposed algorithm using the gradient ascent method to the maximum probability criterion has superior convergence and steady-state MSE performance, and the error samples of the proposed algorithm exhibit more concentrated density functions in blind equalization environments. Simulation results indicate that the proposed training has a potential advantage versus MSE training for the constant modulus approach to blind equalization.

• Journal of Communications and Networks
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• v.12 no.5
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• pp.459-465
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• 2010

A new blind equalization algorithm that is based on maximizing the probability that the constant modulus errors concentrate near zero is proposed. The cost function of the proposed algorithm is to maximize the probability that the equalizer output power is equal to the constant modulus of the transmitted symbols. Two blind information-theoretic learning (ITL) algorithms based on constant modulus error signals are also introduced: One for minimizing the Euclidean probability density function distance and the other for minimizing the constant modulus error entropy. The relations between the algorithms and their characteristics are investigated, and their performance is compared and analyzed through simulations in multi-path channel environments. The proposed algorithm has a lower computational complexity and a faster convergence speed than the other ITL algorithms that are based on a constant modulus error. The error samples of the proposed blind algorithm exhibit more concentrated density functions and superior error rate performance in severe multi-path channel environments when compared with the other algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.85-90
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• 2018

This paper compares the equalization algorithm of CR-MMA (Constellation Reduction-Multi Modulus Algorithm) and FC-MMA (Fast Convergence-Multi Modulus Algorithm) for the compensation of channel's distortion in transmitting the 2 dimensional 16-QAM signals. The CR-MMA adaptive equalizer use the error signal by reduce the nonconstant modulus signal to constant modulus signal in order to updates the tap coefficient, and the FC-MMA adptive equalizer use the error signal applying the modified dispersion constant considering the number of symbol level instead of signal point reduction. These two algorithm are known to its superior to the convergence characteristic among the MMA series equalizer. In this paper, the other equalization performance including the convergence characteristic was compared by computer simulation. As a result of computer simulation, FC-MMA has more good performance in the residual isi, maximum distortion and SER performance than CR-MMA, but not in convergence speed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.27-33
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• 2011

In digital communication system that the Modified Constant Modulus Algorithm (MCMA) reduced the use of the adaptive equalization algorithm to combat the Inter-symbol Interference (ISI). MCMA is relatively brief operation. The major point of MCMA that it only achieves moderate convergence rate and steady state mean square error (MSE). In this paper suggest, MCMA equalization improve the performance with parallel structure. It combines Modified Constant Modulus Algorithm(MCMA) and Modified Decision Directed(MDD) algorithm. By exploiting the inherent structural relationship between the 4-QAM signal's coordinates and 16-QAM signal's coordinates, another style of cost function for Modified Constant Modulus Algorithm(MCMA) is defined and If it happen to offset of received signals and MCMA is poor performance in order to overcome this because the paper combines apply for MCMA and MDD(Modified Decision Direct) algorithm. By computer simulation, we confirmed that the proposed PMCMA-MDD algorithm has the fater convergence rate and steady mean square error than the conventional MCMA.

• 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.

• ETRI Journal
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• v.27 no.3
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• pp.257-266
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• 2005

Many multi-modulus blind equalization algorithms (MMA) have been presented in the past to overcome the undesirable high misadjustment exhibited by the well-known constant modulus algorithm. Some of these MMA schemes, specifically tailored for quadrature amplitude modulation (QAM) constellations, have also been proved to fix the phase offset error without needing any rotator at the end of the equalizer stage. In this paper, a new multi-modulus algorithm is presented for QAM signals. The contribution lies in the technique to incorporate the sliced symbols (outcomes of decision device) in the multi-modulus-based weight adaptation process. The convergence characteristics of the proposed sliced multi-modulus algorithm (S-MMA) is demonstrated by way of simulations, and it is shown that it gives better steady-state performance in terms of residual inter-symbol interference and symbol-error rate. It has also been shown that the proposed algorithm exhibits lesser steady-state misadjustment compared to the best reported MMA.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.465-468
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• 2005

MMA(Multi-Modulus Algorithm) is inferior at a initial equalization in high ISI(intersymbol interference), because it is the inaccurate decision. To improve this probel SMMA(Sliced Multi-Modulus Algorithm) is based on using the MCMA(Modified Constant Modulus Algorithm). SMMA is a improved capability than MMA in high SNR but is inaccurate decision in low SNR. In this paper, We propose some multi-modulus blind equalization algorithm scheme. It is a method of operation in some multi-modulus algorithm which does no obstruct a convergence property at the initial equalization in the low SNR. Proposed algorithm improves the steady-state performance. And it uses residual ISI of the equalizer output in order to decide the optimum switching time between the single modulus and the multi-modulus algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.41-47
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• 2011

This paper is concerned with the DW-MCMA(Dual Weight vector Modified Constant Modulus Algorithm) adaptive equalization algorithm using the dual weight vector in order to improve the convergence characteristic and residual inter-symbol interference which are used as the performance index for an adaptive equalizer. The equalizer is used to reduce the distortion caused by the inter-symbol interference on the wireless and the wired band-limited channel that connect the transmitting system and receiving system. The CMA is widely known as the representative algorithm for equalization. In order to transmitting the mass information with a high speed through the channels, a fast convergence speed in the equalizer performance that is able to minimize overhead needed for equalization is acquired. In this paper, By the computer simulation, we confirmed that the proposed DW-MCMA has the faster convergence speed and the smaller residual inter-symbol interference than the conventional CMA and MCMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.87-92
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• 2017

This paper compares the equalization algorithm of CR-MMA (Constellation Reduction-Multi Modulus Algorithm) and RMMA (Region based Multi Modulus Algorithm) for the compensation of channel's distortion in nonconstant modulus signal. In order to obtain the error signal for adaptive equalization, every signal points are reduced to the constant modulus signal in CR-MMA and every signal points are separated into the 4 regions, then the reductions are performed based on this region in RMMA. These two algorithm based on the reduction principle such as in order to updating the tap coefficient in the adaptive equalization, it has different equalization performance. The computer simulation was performed in order to compare the each equalization performance in this paper. As a result of computer simulation, RMMA has more good performance in the residual isi, maximum distortion and SER performance than CR-MMA, but not in convergence speed.