• 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.

• ETRI Journal
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• v.24 no.3
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• pp.239-246
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• 2002

We investigate an alternative blind adaptive multiuser detection scheme based on a non-canonical linearly constrained constant modulus (LCCM) criterion and prove that, under the constrained condition, the non-canonical linearly constrained constant modulus algorithm (LCCMA) can completely remove multiple -access interference. We further demonstrate that the non-canonical LCCM criterion function is strictly convex in the noise-free state, and that under the constrained condition, it is also strictly convex even where small noise is present. We present a simple method for selecting the constant as well as a stochastic gradient algorithm for implementing our scheme. Numerical simulation results verify the scheme's efficiency.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.19-26
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• 2009

In this paper, a minimum Euclidian distance criterion between error PDF and Dirac delta function is introduced and a constant modulus type blind equalizer algorithm based on the criterion is proposed. The proposed algorithm using constant modulus error in place of actual error term of the criterion has superior convergence and steady state MSE performance, and the error signal of the proposed algorithm exhibits more concentrated density function in blind equalization environments. Simulation results indicate that the proposed method can be a reliable candidate for blind equalizer algorithms for multipoint communications.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.99-104
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• 2015

This paper proposes the RMMA (Region based Multiple Modulus Algorithm) algorithm that is possible to improving the performance of MMA adaptive equalization algorithm in order to the reduction of intersymbol interference occurs at the communication channel. In RMMA algorithm, the output constellation of equalizer are divided by 4 different regions in order to get the error signal for adapting the channel characteristic, and the small error signal is obtained by mapping each region to 4-QAM signal. The conversion effect of constant modulus from nonconstant modulus signal was obtained. In this paper, the adaptive equalization performance of proposed RMMA were evaluated comared to the present MMA. As a result of computer simulation, the convergence speed and residual quantity were improved in residual isi and MD. Especially the superiorities of robustness was confirm in SER performance compared to present MMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.91-97
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• 2016

This paper evaluates the equalization algorithm of FC-MMA (Fast Convergence-Multi Modulus Algorithm) and RMMA (Region based Multi Modulus Algorithm) for the compensation of intersymbol interference which is due to the distortion of communication channel. In order to obtain the error signal for adaptive equalization, the FC-MMA use the modified dispersion constant considering the number of signal symbol, the RMMA separates the 4 region which every symbol points are located, then reduce the symbol point based on this region into constant modulus symbol point. By applying the different principle in order to get the error signal for the updating the tap coefficient of adaptive equalizer, it has the different equalization performance by these error signal. The computer simulation was performed in order to compare the different equalization performance in this paper. The performance index includes the output signal constellation, the residual isi and maximum distortion that is for the convergence characteristics, the SER. As a result of computer simulation, RMMA has more good performance in the residual isi, maximum distortion after in steady state and SER performance than FC-MMA, but not in convergence speed to reach the steady state.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.9
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• pp.1058-1064
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• 2008

In this paper, we proposed a new hybrid interference canceller using the adaptive filter with Grouped CMA(Constant Modulus Algorithm)-LMS(Least Mean Square) algorithm in the RF(Radio Frequency) repeater. The feedback signal generated from transmitter antenna to receiver antenna reduces the performance of the receiver system. The proposed interference canceller has better channel adaptive performance and a lower MSE(Mean Square Error) than conventional structure because it uses the cancellation method of Grouped CMA algorithm. This structure reduces the number of iterations fur the same MSE performance and hardware complexity compared to conventional nonlinear interference canceller. Namely, MSE values of the proposed algorithm were lower than those of LMS algorithm by 2.5 dB and 4 dB according to step sizes. And the proposed algorithm showed fast speed of convergence and similar MSE performance compared to VSS(Variable Step Size)-LMS algorithm.

• The Journal of Information Technology
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• v.1 no.2
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• pp.39-53
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• 1998

The CMA and MCMA adaptive blind equalization algorithm has an inevitable error caused by mismatching between the original constellation at the steady state after the equalization and the unique constellation. This problem is due to considering the new type constellation(constant modulus, reduced constellation) as desired constellation. In this paper, we propose a new adaptive blind equalization algorithm which can reach to the steady state with rapid convergence speed and achive the improvement of error value in the steady state. The Proposed algorithm has a new error function using the decided original constellation instead of the reduced constellation. By computer simulation, it is comfirmed that the proposed algorithm has the performance superiority in terms of residual ISI and convergence speed compared with the adaptive blind equalization algorithm of CMA family, Constant Modulus Algorithm with Carrier Phase Recovery and Modified CMA(MCMA).

• 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 Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2172-2177
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• 2015

The DF-MZEP-CME (decision feedback - maximum zero-error probability for constant modulus errors) algorithm that makes the probability for constant modulus error (CME) close to zero and employs decision feedback (DF) structures shows more improved performance in channel distortion compensation. However the DF-MZEP-CME algorithm has a computational complexity proportional to a sample size for probability estimation and this property plays a role of an obstacle in practical implementation. In this paper, the gradient of DF-MZEP-CME is proposed to be estimated recursively and shown to solve the computational problem by making the algorithm independent of the sample size. For a sample size N, the conventional method has 10N multiplications but the proposed has only 20 regardless of N. Also the recursive gradient estimation for weight update is kept in continuity from the initial state to the steady state without any error propagation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.107-113
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• 2019

This paper proposes the Hybrid-CRMMA adaptive equalization algorithm that is possible to improves the performance of CR-MMA based on adaptive modulus and adaptive stepsize. The 16-QAM nonconstant modulus signal is reduced to 4-QAM constant modulus signal, and the error signal were obtained based on the fixed statistic modulus of transmitted signal. It is possible to improving the currently MMA adaptive equalization performance. The proposed Hybrid-CRMMA composed of adaptive modulus which is propotional to the power of equalizer output and adaptive stepsize which is function of the nonlinearties of error signal, and its improved equalization performance were confirmed by computer simulation. For this purpose, the output signal constellation, the residual isi and maximum distortion and MSE that is for the convergence characteristics, the SER that is meaning the robustness of external noise of algorithm were used. As a result of computer simulation, it was confirmed that the proposed Hybrid-CRMMA has more superior performance in every index compared to currently CR-MMA.