• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.121-127
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• 2010

This paper relates with the improved CMA blind adaptive equalization algorithm which uses the constellation matching method that improve the inverse modelling efficiency of a communication channel compared to the present CMA blind adaptive equalizer. The amplitude distortion can be compensated in the present CMA blind adaptive equalizer which is used for the reduction of intersymbol interference by distortion that generate such as a band limited wireless mobile channel, but in the improved adaptive alogorithm operates with the minimize the amplitude phase distortion in the output of equalizer by applying the cost function that is composition of additional signal constellation matching error terms. In order to evaluation of the inverse modeling efficiency of improved algorithm, the residual intersymbol interference and recovered signal constellation were compared by computer simulation. As a result of comparion of computer simulation, the improved algorithm has a good stability in the residual intersymbol interference in the steady state, but it has a slow convergence rate in the adaptation state in initial state.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.11-17
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• 2009

Blind equalization techniques have been used in multipoint communication on which the research on the internet has focused. In this paper, a criterion of minimizing Euclidian Distance between two PDFs for adaptive blind equalizers has been presented. In order for ED expressed with Parzen PDFs to be minimized, we propose to use a set of randomly generated desired symbols at the receiver so that the PDF of the generated symbols matches that of the transmitted symbols. From the simulation results, the proposed method has shown superior error performance even in severe channel environments in which CMA has shown severe performance degradation. This indicates that the proposed algorithm can be considered relatively insensitive to ESR variations compared to CMA. As a field of ITL, ED minimization using Parzen PDFs has shown possibilities of being successfully applied to blind equalization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.7
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• pp.1364-1373
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• 1994

In this thesis, an algorithm for fast convergence to the steady state and for achieving an improved MSE in blind adaptive equalizers is proposed. The conventional radius-directed algorithm can be transformed into an algorithm that provides effective blind convergence in the aspect of the MSE as the convergence speed. This can be achieved through altering the stop and go algorithm. The performance of the new algorithm is analyzed and compared with the two conventional algorithms, such as the CMA and the stop and go algorithm. The experimental results show the superiority of the new algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4B
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• pp.237-244
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• 2003

This paper presents the design of a QPSK/16-QAM downstreams receiver chip. The proposed chip consists of a blind equalizer, a timing recovery block and a carrier recovery block. The blind equalizer uses a DFE sturucture using CMA(Constant Module Algorithm). The symbol timing recovery uses the modified parabolic interpolator. The decision-directed carrier recovery is used to remove the carrier frequency offset, phase offset and phase jitter. The implemented LMDS receiver can support four data rates, 10, 20, 30 and 40 Mbps and can accommodate the symbol rate up to 10 Mbaud. This symbol rate is faster than existing QAM receivers.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.52-58
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• 2013

This paper proposes an adaptive algorithm based on a method of dynamic error signal generation suitable for signal state by examining the equalizer output signal in blind equalization. In the proposed method, it estimates the error signals using single modulus and multiple modulus each effective to the early stage of equalization or steady-state, and it generates a new error signal from the two error estimates. Two equalizer structures are implemented and their performances are compared: 1-equalizer structure that generates a new error signal by combining the two error estimates weightedly and updates the equalizer using this, and 2-equalizer structure that updates two equalizers respectively depending on the weights of the two error signals. In the proposed method, as the error signals were generated optimally before and after the initial convergence respectively, it was confirmed by computer simulations that the equalizer was updated effectively.

• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1284-1294
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• 2007

In this paper, a blind nonlinear channel equalization is implemented by using a Modified Fuzzy C-Means (MFCM) algorithm. The proposed MFCM searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.1957-1967
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• 1997

Adaptive channel equlization accomplished without resorting to a training sequence is known as blind equalization. In this paper, in order to reduce the speed of the convergence and the steady-state mean squared error simultaneously, we propose the multi-stage RD(radius-directed) algorithm derived from the combination of the constant modulus algorithm and the radius-directed algorithm. In the starting stage, multi-stage RD algorithm are identical to the constant modulus algorithm which guarantees the convergence of the equalizer. As the blind identical to the constant modulus algorithm which guarantees the convergence of the equalizer. As the blind equalizer converges, the number of the level of the quantizers is increased gradually, so that the proposed algorithm operate identical to the radius-directed algorithm which leads to the low error power after the covnergence. Therefore, the multi-stage RD algorithm obtains fast convergence rage and low steady stage mean square error.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.3
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• pp.419-424
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• 2015

The Decision-directed (DD) algorithm is known to be not effective to initialize a blind equalizer in the channel conditions when the eye diagram of received signals is completely closed because it can not open the eye diagram enough. In this paper, we propose a new error to replace the error of the conventional DD algorithm. The new DD error is the conventional DD error scaled by the modulus of symbol decision, new DD algorithm using this error is effective to open the closed eye diagram in early stage of equalization unlike the conventional DD. The new DD algorithm appling the new error is showed excellent convergence characteristics as compared to the CMA widely used in blind initialization, particularly, is useful for equalization of signals having multimodulus. The performance of the new DD algorithm is verified through the simulation for the higher-order QAM signals.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3660-3665
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• 2012

For blind equalization, it is necessary to open an eye pattern quickly in the early stage of equalization, after that it is important to lower an error level of equalizer output signal. This paper discusses coarse error estimation using signal points specifically determined and fine error estimation using original signal constellation, and proposes two suggestions for how to take advantage of the two error estimation methods. The two error estimates, respectively, are effective to quickly open an eye pattern in the state of eye pattern closed, or to lower the level of an error in the steady-state after the eye pattern opening. Two blind equalization algorithms are proposed and their performances are compared, which select one of the two error estimates depending on the state of convergence of the equalizer, or combine two errors weightedly according to the relative reliabilities of the two error estimates, and calculate the new error.