• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.5
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• pp.459-464
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• 2016

The mobile communication service is widely used and the repeaters is rapidly increasing because of the extending service areas. we propose a new Signed CMA(: Constant Modulus Algorithm) algorithm for ICS(: Interference Cancellation System) as a larger service area of mobile communication service. The proposed Signed CMA algorithm improved performances by adjusting step size values. We showed that the proposed algorithm could improve the Mean Square Error(: MSE) performance of Signed CMA. MATLAB(: Matrix Laboratory) is employed to analyze the proposed algorithm and to compare it with the experimental results. At the convergence of 1000 iteration state, the MSE(: Mean Square Error) performance of the proposed Signed CMA algorithm with step size of 0.0065 is about 5 dB better than the conventional CMA algorithm.

• Journal of Internet Computing and Services
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• v.11 no.5
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• pp.1-8
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• 2010

This paper presentsthe performance study of blind equalizer algorithms for impulsive-noise environments based on Gaussian kernel and constant modulus error(CME). Constant modulus algorithm(CMA) based on CME and mean squared error(MSE) criterion fails in impulsive noise environment. Correntropy blind method recently introduced for impulsive-noise resistance has shown in PAM system not very satisfying results. It is revealed in theoretical and simulation analysis that the maximization of zero-error probability based on CME(MZEP-CME) originally proposed for Gaussian noise environments produces superior performance in impulsive noise channels as well. Gaussian kernel of MZEP-CME has a strong effect of becoming insensitive to the large differences between the power of impulse-infected outputs and the constant modulus value.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.27-32
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• 2020

This paper compare the adaptive equalization performance according to the values of adaptive step variation speed for adapting in VS-CCA (Variable Stepsize-Compact Constellation Algorithm) based on nonlinear function function of error signal. The VS-CCA algorithm compacts the 16-QAM nonconstant modulus signal into the 4 groups of 4-QAM constant modulus signal constellation in quadature plane, then the error signal is generated using the constant modulus of transmitted signal statistics. The adaptive equalizer coefficient were updated in order to achieve the minimum cost function by varying step based on the nonlinear function of error signal. In this time, the instantaneous adaptive step is determined according to the value of step variation speed of nonlinear function and the different equalization performance were obtained according to the step variation speed value. The equalizer internal index and external index which represents the robustness of external noise were used for the performance comparison index. As a result of computer simulation, it was confirmed that the value of variation speed less than 1.0 give more superior in every performance index compared to the greater than 1.0 in steady state.

• Journal of Internet Computing and Services
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• v.15 no.5
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• pp.17-24
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• 2014

Blind algorithms designed to maximize the probability that constant modulus errors become zero carry out some summation operations for a set of constant modulus errors at an iteration time inducing heavy complexity. For the purpose of reducing this computational burden induced from the summation, a new approach to the estimation of the zero-error probability (ZEP) of constant modulus errors (CME) and its gradient is proposed in this paper. The ZEP of CME at the next iteration time is shown to be calculated recursively based on the currently calculated ZEP of CME. It also is shown that the gradient for the weight update of the algorithm can be obtained by differentiating the ZEP of CME estimated recursively. From the simulation results that the proposed estimation method of ZEP-CME and its gradient produces exactly the same estimation results with a significantly reduced computational complexity as the block-processing method does.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.85-90
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• 2018

This paper compares the adaptive eualization performance of CR-MMA (Constellation Reduction-MMA) and CR-MMA (Constellation Matching-MMA) in order to minimization of intersymbol interference that is occur in channel for 2-dimensional QAM signal. For obtain the error signal in order to updating the tap coefficient of conventional adaptive equalization algorithm MMA, the CR-MMA converts the constellation reduction concept of high order 2-dimensional QAM nonconstant modulus signal to constant modulus signal and the CM-MMA use the constellation matchine error concept in order to force the matching the $2^{nd}$ and $4^{th}$ cumulant of equalizer output and transmitted signal constellation. By applying the different method for getting the error signal, these algorithm are possible to obtain the improved equalization performance compared to the conventional MMA algorithm, the improved performance of CR-MMA and CM-MMA were compared by computer simulation in this paper. As a result of simulation, the CM-MMA has more better performance in the equalizer internal performance than CR-MMA, but not in equalizer external performance as in SER.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.152-159
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• 2005

For high-speed data communication in band-limited channels, main of the bit error are fading and ISI(Inter-Symbol Interference). The common way of dealing with ISI is using equalization in the receiver. In this thesis, channel adaptive equalizer which uses Fuzzy Stochastic Gradient(FSG) and Constant Modulus Algorithm(CMA) is nonlinear equalizer, or Blind equalizer, that works directly on the signals with no training sequences required. This equalizer employs Takagi-Sugeno's fuzzy model that uses the FSG algorithm, to automatically regulate the step size of the descent gradient vector, combining fast convergence rate and low mean square error(MSE), and the CMA which is a special case of Godard's algorithm, to having multiple dispersion constants($R_p$).

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.2
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• pp.17-28
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• 2002

Recently, the study on non-linear equalization, self-recovering equalization using the neural Network structure or Fuzzy logic, is lively in progress. In this thesis, if the value of error difference is large, coefficient adaptation rate is bigger, and if being small, it is smaller. We proposed the new FSG(Fuzzy Stochastic Gradient)/CMA algorithm combining TS(Tagaki-Sugeno) fuzzy model having fast convergence rate and low mean square error(MSE) and CMA(Constant Modulus Algorithm) which is prone to ISI and insensitive to phase alteration. As a simulation result of the designed channel adaptive equalizer using the proposed FSG/CMA algorithm, it is shown that SNR is improved about 3.5dB comparing to the conventional algorithm. 

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.238-241
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• 2000

This paper describes an equalizer using the DFE (Decision Feedback Equalizer) structure, CMA. (Constant Modulus Algorithm) and LMS (Least Mean Square) algorithms. We employ high speed multipliers, square logics and many CSAs (Carry Save Adder) for high speed operations. We have developed floating-point models and fixed-point models using the COSSAP$\^$TM/ CAD tool and developed VHDL models. We have peformed logic synthesis using the SYNOPSYS$\^$TM/ CAD tool and the SAMSUNG 0.5 $\mu\textrm{m}$ standard cell library (STD80). The total number of gates is about 130,000.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10B
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• pp.1760-1768
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• 2000

Blind Equalization Method without training sequences is proposed for channel efficiency in mobile communication system for asynchronous multi-user DS-CDMA. the risk of mis-convergence of weak-power users is increased because of small regions of convergence in case of near-far effect in CMA(Constant Modulus Algorithm) which is the simplest has high performance and widely implemented. In despite the problem a equalization using Newton method has higher performance than a conventional method in squared error and eye-pattern.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.115-120
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• 2016

This paper deals with AM-SMMA (Adaptive Modulus-SMMA) adaptive equalization algorithm that is possible to improves the equalization performance using adaptive modulus which is propotional to the output signal power of equalizer in the current SMMA algorithm. The fixed statistic modulus of transmitted QAM signal is used in current SMMA algorithm in order to generate the error signal for updating the tap coefficient of equalizer. The adaptive modulus which is propotion to the equalizer output signal power is used in the proposed AM-SMMA. The computer simulation was performed in order to confirm the improved equalization performance of proposed algorithm. 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, the residual isi, maximum distortion are better in the small weighting values. But in SER performance is better in the large weighting values.