• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.136-139
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• 2010

We derived Stop-and-go normalized DD, dual-mode normalized Sato, dual-mode NCMA blind equalization algorithm for complex data in this research. And then, the convergence characteristics of the proposed SG-NDD, dual-mode NSato blind equalization algorithms are compared with those of SG-DD, dual-mode Sato algorithms. In general, the normalized blind equalization algorithms have better convergence characteristics than the conventional algorithms.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.5
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• pp.14-23
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• 1995

A new dual-mode algorithm for blind equalization of quadrature amplitude modulation (QAM) signals is proposed. To solve the problem that the constant modulus algorithm (CMA) converges to the constellation with the arbitrary phase rotation, with the modification of the CMA, the proposed algorithm accomplishes blind equalization and carrier phase recovery simultaneously. In addition, the dual-mode algorithm combining the modified constant modulus algorithm (MCMA) with decision-directed (DD) algorithm achieves the performance enhancement of blind convergence speed and steady-state residual ISI. So we can refer the proposed algorithm to as a scheme for joint blind equalization and carrier phase recovery. Simulation results for i.i.d. input signals confirm that the dual-mode algorithm results in faster convergence speed, samller residual ISI, and better carrier phase recovery than those of the CMA and DD algorithm without any significant increase in computational complexity.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.627-630
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• 1998

In this study, we derived stop-and-go normalized DD, dual-mode normalized sato, dual-mode NCMA blind equalization algorithm for complex data. and then, the convergence characteristics of the proposed SG-NDD, dual-mode NSato blind equalization algorithms are compared with those of SG-DD, dual-mode sato algorithm. In genral, the normalized blind equalization algorithms have better convergence characteristics than the conventional algorithms.

• 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.

• 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 the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.89-95
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• 2016

In this paper, we propose a dual-mode blind equalization algorithm that two of the blind equalization algorithm using the size of the decision-directed error signal is automatically switched. The proposed algorithm has a faster convergence speed due to operation of the MSAGF-SMMA with large fixed step-size mainly in the initial equalization. After the equalization has been made to some extent, the proposed algorithm has a smaller residual error in the steady- state by operation of the MSAGF-SMMA with a variable step-size mainly. The variable step-size is determined by multiplying the size of the decision-directed error signal of a fixed step-size. In this paper, we analyze the performance of the proposed algorithm. The computer simulation results demonstrate that the proposed algorithm has a significantly improved performance in terms of a residual inter-symbol interference and residual error in the steady-state compared with the MMA, SMMA, and MSAGF-SMMA.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3138-3140
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• 1999

We propose a robust blind equalization algorithm based on dual-mode algorithm which incorporates a stop-and-go technique. The constant modulus algorithm(CMA) exhibits very slow convergence when applied to QAM signals and generates phase error. We show that convergence properties of the dual-mode MCMA can be significantly improved by simply adding a stop-and-go technique. To speed up the convergence rate, the TMA-MCMA operates in triple mode that is based on the dual-mode of the MCMA incorporated with the tap-updating control modes of the SGA.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.269-274
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• 2004

In this paper, proposed is the dual-mode algorithm of blind decision feedback equalizer (DFE) for digital terrestrial television signals. According to channel impairments, the proposed dual-mode algorithm for blind DFE operates in decision-directed mode or in blind mode of operation. The error signals being used in tap update of the equalizer are generated in the best mode of operations, so that the confidence of equalizer tap coefficient update is more accurate. As a result, it is possible to track the channel characteristics variations by automatic switching over between two modes of operations. For 8-level vestigial sideband modulated digital television signals, the mean square errors and symbol error rates of the proposed algorithm are compared with those of conventional methods. And the usability of the proposed scheme is assessed by computer simulations under various static and dynamic multipath channel environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.2005-2013
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• 1997

The MCMA adaptive blind equalization algorithm has a excellent phase correction capabilities in addition to channel amplitude equalization, but has an inevitable error by mismatching between the original constellation points in arriving at the perfect equalization since unique new type constellation points are used as desired response instead of original constellation points and follows the slow convergence speed of CMA. In this paper, We propose an adaptive blind equalization algorithm with dual-mode, which has decision regions. Inside the decision regions, it operates as considering the moudlus of original data symbol point and outside the decision region, it operates as considerin gthe modulus of new constellation points. The proposed algorithm has a lower error in the steady state and rapid convergence speed toward steady state using the original data symbol points instead of new constellation points in the decision regions. From computer simulation, we confirm that the propposed algorithm has the performance superiority in residual ISI, convergence speed compared with the cnventional adaptive blind equalization algorithms, CMA, MCMA, Stop-and-Go algorithm.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.1037-1045
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• 1999

We propose two new classes of robust blind equalization algorithms against abrupt changes of channel conditions, which we call a triple-mode algorithm(TMA) and an automatic switch-over algorithm(ASA). The conventional DMGSA exhibits slow convergence rates due to the incorrect equalizer tap-updating process under the severe channel conditions. In order to speed up the convergence process, the TMA operates in triple-mode that is based on the dual-mode of the DMGSA incorporated with the tap-updating control modes of the SGA as well as the MSGA. Without resorting to the decision region for selecting the operation mode in the TMA, the ASA automatically switches the blind mode to the smoother conventional decision-directed mode. The ASA uses the error functional that is the weighted sum of the Generalized Sato error and the decision-directed error, where the weights correspond to the channel conditions. Test results on 16-QAM and 8-VSB datas confirm that the TMA and the ASA perform well under the sudden changes of channel conditions.