• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.10
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• pp.1104-1111
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• 2003

The paper presents an algorithm for the compensation of gain and phase imbalances to exist between I-phase and Q-phase signal at direct conversion receiver. We propose a gain and phase imbalances blind equalization compensation algorithm by using variable step-size adaptive loop at direct conversion receiver. The blind equalization schemes have trade-off between convergence speed and jitter effect for the compensation of gain and phase imbalance. We propose the variable step-size adaptive loop method, which varies the loop coefficients according to errors, for recovering these problem. By using variable step-size adaptive loops, we propose to speed up the convergence process and reduce the jitter effect and simulation results show that the algorithm compensates signal loss and speeds up convergence time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5036-5041
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• 2010

This paper introduces the complex-version of an Euclidean distance minimization algorithm based on a set of delta functions. The algorithm is analyzed to be able to compensate inherently the channel phase distortion caused by inferior complex channels. Also this algorithm has a relatively small size of Gaussian kernel compared to the conventional method of using a randomly generated symbol set. This characteristic implies that the information potential between desired symbol and output is higher so that the algorithm forces output more strongly to gather close to the desired symbol. Based on 16 QAM system and phase distorted complex-channel models, mean squared error (MSE) performance and concentration performance of output symbol points are evaluated. Simulation results show that the algorithm compensates channel phase distortion effectively in constellation performance and about 5 dB enhancement in steady state MSE performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.7-13
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• 2012

The performance of blind equalization algorithm ISCA was compared with MSCA that is used for the minimization of the inter symbol interference which occurs in the time dispersive communication channel for digital transmission. Because of the non-linearities of a magnitude and phase transfer characteristics of a communication channel, the transmitting signal will be received that band limited and time dispersived. Therefore the distortion was compensated by using the self adaptive equalizer at the receiving side, then passing through the detector for the decision of "1" or "0". At this time the Constellation Dependent Constant is played an important role in the adaptive equalizer used on the receiver. In order to calculation of this constant, the ISCA and MSCA was used the second order statistics. The ISCA and MSCA which are possible to compensation of mensioned transfer function simulataneously, are improved the performance of original SCA algorithm and then was compared the performance by computer simulation. For this, the recovered constellation, residual isi and MSE was used, and a result of performance comparison, the ISCA algorithm has better than the MSCA in every performance index. But on the steady state of equalizer, the variation of performance due to the CME terms in the MSCA equalization algorithm was less than the ISCA, so MSCA has better stability.

• 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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• 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.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.43-46
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• 1999

Blind equalizers recover the transmitted data using signal's statistical characteristics only. Because of its computational simplicity and fast convergence rate, CMA is widely used in practice. Blind equalizers, however, converge much slowly than conventional equalizers which use the training signals. In order to improve the convergence rate, many modified blind equalization algorithms have been proposed. Among those, Normalized CMA (NCMA) was applied to increase the convergence rate by using the large step size. Unfortunately it can only be applied for the constant modulus signal constellation scheme. this paper, we propose the Selective NCMA (SNCMA) that improve the convergence rate of blind equalization algorithms by using NCMA for non-constant modulus signalling method such as QAM constellation. We achieved fast start-up convergence rate and reduced steady-state residual error.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.476-483
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• 2010

If the data are pre-whitened, then gradient adaptive algorithms which are simpler than higher order statistics algorithms can be used in adaptive blind signal estimation. In this paper, we propose a blind subband affine projection algorithm for multiple-input multiple-output adaptive equalization in the blind environments. All of the adaptive filters in subband affine projection equalization are decomposed to polyphase components, and the coefficients of the decomposed adaptive sub-filters are updated by defining the multiple cost functions. An infinite impulse response filter bank is designed for the data pre-whitening. Pre-whitening procedure through subband filtering can speed up the convergence rate of the algorithm without additional computation. Simulation results are presented showing the proposed algorithm's convergence rate, blind equalization and blind signal separation performances.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7A
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• pp.978-985
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• 2000

Blind equalizers recover the transmitted data using statistical characteristics of the signal alone. Among many alternatives, steepest gradient descent type algorithms such as the CMA and Sato algorithm are most widely utilized in practice. In this paper we propose a dual-mode NCMA algorithm, which combines the advantages of the dual mode CMA and Normalized CMA (NCMA) with the dual mode phase recovery algorithm. In addition, we perform computer simulations to demonstrate the performance improvement of the proposed algorithm with a QAM system. Simulation results show that the presented algorithm has a faster convergence speed and smaller steady-state residual error than the CMA and dual-mode CMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.107-114
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• 2012

In this paper, the concerned existing blind equalizer convergence rate and residual inter-symbol interference using constellation reduced and cost function by separation the real part and an imaginary part, the dual structure CR-CMA(constellation Reduction CMA). The CMA methed compensates amplitude but does no compensate phase, On the other hand, The CMA method compensates both the amplitude and the phase but it has the convergence rate problem, and the 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 part and imaginary part components. Proposal a new method that the dual structure of CR-CMA, the cost function and error function and respectively calculating the real part and imaginary part components can advantages by improving the CMA and the MCMA algorithms so that the amplitude and phase retrieval and constellation reduce the residual ISI and faster convergence rate and performance is good SER (Symbol Error Ratio) was confirmed by computer simulations.