• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.445-447
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• 2005

MCMA(modified constant modulus algorithm) accomplishes blind equalization and carrier phase recovery simultaneously. But, the error level of MCMA is not zero when the equalizer converges completely. Because the MCMA uses a special signal point instead of a original signal point. MCMA-DO(decision-directed) improves the steady-state performance but the performance of equalizer is decided by switching time between the MCMA and the DD. In this paper, according to the residual ISI(intersymbol interference) of the equalizer output, the most suitable switching time is decided automatically.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6B
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• pp.1074-1081
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• 2000

In this paper, in order to speed up the convergence process and improve the steady mean square error simultaneously, we propose the Stop-and-Go Dual Mode Modified Constant Modulus Algorithm(SAG DM MCMA) for adaptive blind channel equalization of high order QAM. The proposed algorithm is a hybrid scheme of the Modified CMA that treat error signals with real and imaginary components of the equalizer output, the concept of dual mode CMA, and Stop-and-Go algorithm. As a result it can prevent blind equalization from converging to incorrect direction and simultaneously operates reliably for tap weight adaptation. We demonstrate via simulation that the proposed algorithm achieves lower steady state mean square error and residual ISI than the conventional algorithms under high order QAM signals and severe channel environment.

• The Journal of Information Technology
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• v.2 no.1
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• pp.103-113
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• 1999

In this paper, we propose th soft decision-directed sto-and-go algorithm combining a concept of the stop-and-go algorithm with soft decision-directed algorithm. The proposed algorithm has an enhanced equalization performance according to using the more confidential error signal than two algorithms. By computer simulation, it is confirmed 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, Modified CMA(MCMA), Stop-and Go algorithm and simplified 50ft decision-directed algorithm.

• The KIPS Transactions:PartC
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• v.13C no.3 s.106
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• pp.369-374
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• 2006

This paper related with the performance improvement of adaptive equalizer that is a based on the tricepstrum eqalization algorithm by using the received signal. Adaptive equalizer used for the improvement of communication performance, like as high speed, maintain of synchronization, BER, at the receive side in the environment of communication channel of the presence of the aditive noise, phase distortion and frequency selective fading, mainly. It's characteristics are nearly same as the inverse characterstics of the communication channel. In this paper, the TEA algorithm using the HOS and the 16-QAM which is 2-dimensional signaling method for being considered signal was used. For the precoding of 16-QAM singnal in the assignment of the signal costellation, Gray code was used, and the improvement of performance was gained by computer simulation in the residual intersymbol interence and mean squared error which is representive measurement of adaptive equalizer.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.127-133
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• 2012

In this paper, the concerned CMA (Constant Modulus Algorithm) adaptive equalizer convergence rate and residual inter-symbol interference using cost function in order to improved to the ACMA (Advanced CMA). The CMA method compensates amplitude but does not compensate phase. On the other hand, The RCA (Reduced Constellation Algorithm) method compensates both the amplitude and the phase but it has the convergence rate problem. MCMA method is a way to solve the phase problem of CMA method compensates both the amplitude and the phase after respectively calculating the real and imaginary components. But it is more than poor CMA method in the complexity of hardware and the compensation performance. The cost function can advantages by improving the CMA and a MCMA (Modified CMA) equalizer so that the amplitude and phase retrieval the equalization steady-state to reduce the error by using ISI and faster convergence rate and performance is good SER (Symbol Error Ratio) was confirmed by computer simulations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.77-82
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• 2018

This paper is concerned with the performance analysis of a modified stop-and-go generalized multi-modulus algorithm (MSAG-GMMA) adaptive blind equalization algorithm with variable step size. The proposed algorithm multiplies the fixed step size by the error signal of the decision-oriented algorithm in the equalization coefficient update equation, and changes the step size according to the error size. Also, the MSAG-GMMA having a fixed step size is operated so as to maintain a fast convergence speed from a certain threshold to a steady state by determining the error signal size of the decision-directed algorithm, and when the MSAG-GMMA to work To evaluate the performance of the proposed algorithm, we use the ensemble ISI, ensemble-averaged MSE, and equalized constellation obtained from the output of the equalizer as the performance index. Simulation results show that the proposed algorithm has faster convergence speeds than MMA, GMMA, and MSAG-GMMA and has a small residual error in steady state.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.9 no.6
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• pp.746-760
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• 1998

In this paper, an adaptive RSSD(reduced-state sequence detection) receiver is proposed for the purpose of reducing the complexity and decision delay of the adaptive MLSD(maximum-likelihood sequence detection) receiver in the mobile satellite channel. The RSSD receiver reconstructs the trellis with a reduced number of states. The performance degradation due to the reduced states is compensated by modifying the branch metric calculation which uses the symbols in each path memory to estimate the residual ISI(intersymbol interference) terms. The structure of the proposed adaptive RSSD is a modified RSSD utilizing a per-survivor processing as well as the symbol-aided method and a channel estimation using the tentative data sequences. The complexity and performance of the proposed adaptive RSSD are controlled by the number of system states and ISI cancelers and the inserting period of the known symbols. In spite of a suboptimal alternative receiver compared to the adaptive MLSD receiver, the proposed adaptive RSSD receiver is able to reduce the complexity significantly and track the time-varying channel fast and reliably.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.105-111
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• 2017

This paper compares the SE-MMA (Signed Error-MMA) and QE-MMA (Quantized Error-MMA) adaptive equalization algorithm in order to compensates the intersymbol interference due to channel in the transmission of spectral efficient nonconstant modulus signal such as 16-QAM. In the currently MMA adaptive equalizer, the error signal is needed for the updating the tap coefficient. The SE-MMA uses the polarity of error signal for reduce the computational operation in that process, the QE-MMA consider the this polarity and finite bit power-of-2 quantized component in that process, so they has different equalization performance. In order to comparing these performance, the computer simulation was performed in the same channel and environment, the output signal constellation of equalizer, residual isi and maximum distortion, MSE, SER were applied. As a result of computer simulation, the QE-MMA have more superior performance than the SE-MMA in every performance index.

• The Journal of the Acoustical Society of Korea
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• v.31 no.1
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• pp.1-10
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• 2012

The linear and decision-feedback equalization can mitigate time-varying intersymbol interference (ISI) caused by time-varying multipath propagation for underwater acoustic channels. The perfect elimination of interference components, however, is difficult using the linear equalization and the decision feedback equalizer has an error propagation problem. To overcome these shortcomings, this paper proposes an equalizer mode selection method using training sequences. The proposed method selects an equalization mode corresponding to the signal-to-noise ratio (SNR). If the SNR is low, the proposed system operates the linear equalizer for preventing the error propagation and if the SNR is high, the decision feedback equalizer for eliminating the residual ISI. Therefore, the proposed method can improve the error performance compared to the conventional equalizers. The computer simulation shows the proposed method improves the bit error performance using practical underwater channels responses acquired from the sea experiment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.57-62
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• 2019

This paper evaluates the QE-MMA (Quantized Error-MMA) adaptive equalization algorithm by the number of quantizer in order to compensates the intersymbol interference due to channel in the transmission of high spectral efficient nonconstant modulus signal. In the adaptive equalizer, the error signal is needed for the updating the tap coefficient, the QE-MMA uses the polarity of error signal and correlation multiplier that condered nonlinear finite bit power-of-two quantizing component in order to convinience of H/W implementation. The different adaptive equalization performance were obtained by the number of quantizer, these performance were evaluated by the computer simulation. For this, the equalizer output signal constellation, residual isi, maximum distortion, MSE, SER were applied as a performance index. As a result of computer simulation, it improved equalization performance and reduced equalization noise were obtained in the steady state by using large quantizer bit numbers, but gives slow in convergence speed for reaching steady state.