• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.75-78
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• 1999

The iterative usage of soft outputs increases the performance of digital radio receiver. The feedback of reliability information reduces the channel estimation errors and increases the performance of equalization. This paper investigates the turbo equalization techniques for wireless cellular systems over continuous time varying channel. Simulation results over a GSM channel were presented.

• Journal of Communications and Networks
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• v.11 no.5
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• pp.473-479
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• 2009

Conventional frequency domain equalization (FDE) schemes were originally devised for quasi-static channels. Thus, such equalization schemes could suffer from significant performance degradation in fast-fading channels. This paper proposes a frequency domain equalization algorithm to mitigate the effect of fast time-varying fading. First, a mathematical expression is derived to quantify the total interference resulting from the time variation of the channel. Then, the proposed approach attempts to eliminate the effect of time-variations of the channel. This cancellation allows efficient use of the classical FDE structures in fast time-varying fading environments, although they are built upon the quasi-static channel model. Simulation results of bit-error-rate performance are provided to demonstrate the effectiveness of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.11
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• pp.2116-2132
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• 1994

In this paper, channel equalization techniques for full-digital HDTV systems are investigated Conventional equalization methods are surveyed and several channel are modeled for computer simulation. A VS-LMS (Variable Step size Least Mean Square) algorithm using the time constant concept is proposed and its performance is compared. Several equalization techniques for HDTV systems are simulated based on various channel models, and their characteristics are analyzed. Also the equalizer using fixed-point operations is simulated and its filter structure suitable for high bit rate transmission is also studied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.1
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• pp.64-71
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• 1997

Digital communication channels are imparied by linear effects such as dispersion, ISI(intersymbol Interference), fading phenomenon etc. But, the practical channel equalization system is required to design for compensating the nonlinear distortion caused by harmonic distortion etc. This paper is a study on the performance of nonlinear channel equalization using RBF(Radial Basis Funclion) network, which has the equivalent structure to the optimal Basian filter. Expecially, the variance of RBF network is modifiedby nonlinear polynomial filters to compare the convergence characteristic of nonlinear channel equalization. Experimental results show that the modified RBF network achieves the faster convergence property than conventional RBF network. Moreover, the RBF network ofhigher order variance modified represents the better performance than that of lower order variance in the bandpass channels and second/third order polynomial channels.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.3
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• pp.169-173
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• 2012

This paper investigates the performance of Turbo equalization in wireless multipath channels. Turbo equalization mainly consists of a SISO(soft-in soft-out) equalizer and a SISO decoder. Iterative channel estimators can improve the accuracy of channel estimates by soft information fed back from the SISO decoder. Comparing iterative channel estimators with LMS(least mean square) and RLS(recursive least squares) algorithms, which are the most common algorithms to estimate and track a time-varying channel impulse response, the iterative channel estimator with RLS converges more faster than the one with LMS. However, the difference of BER(bit error rate) performances gradually decreases as the number of iterations for Turbo equalization increases.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.383-391
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• 2009

In this paper, blind equalization using a modified Fuzzy C-Means algorithm with Gaussian Weights (MFCM_GW) is attempted to the heavy noise-corrupted channels. The proposed algorithm can deal with both of linear and nonlinear channels, because it searches for the optimal channel output states of a channel instead of estimating the channel parameters in a direct manner. In contrast to the common Euclidean distance in Fuzzy C-Means (FCM), the use of the Bayesian likelihood fitness function and the Gaussian weighted partition matrix is exploited in its search procedure. The selected channel states by MFCM_GW are always close to the optimal set of a channel even the additive white Gaussian noise (AWGN) is heavily corrupted in it. Simulation studies demonstrate that the performance of the proposed method is relatively superior to existing genetic algorithm (GA) and conventional FCM based methods in terms of accuracy and speed.

• Journal of information and communication convergence engineering
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• v.5 no.1
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• pp.35-41
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• 2007

In this paper, a modified Fuzzy C-Means (MFCM) algorithm is presented for nonlinear blind channel equalization. The proposed MFCM searches the optimal channel output states of a nonlinear channel, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. In its searching procedure, all of the possible desired channel states are constructed with the elements of estimated channel output states. The desired state with the maximum Bayesian fitness is selected 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.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.609-617
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• 2010

This paper is concerned with the use of a selforganizing map (SOM) to estimate the desired channel states of an unknown digital communication channel for blind equalization. The modification of SOM is accomplished by using the Bayesian likelihood fitness function and the relation between the desired channel states and channel output states. At the end of each clustering epoch, a set of estimated clusters for an unknown channel is chosen as a set of pre-defined desired channel states, and used to extract the channel output states. Next, all of the possible desired channel states are constructed by considering the combinations of extracted channel output states, and a set of the desired states characterized by the maximal value of the Bayesian fitness is subsequently selected for the next SOM clustering epoch. This modification of SOM makes it possible to search the optimal desired channel states of an unknown channel. In simulations, binary signals are generated at random with Gaussian noise, and both linear and nonlinear channels are evaluated. The performance of the proposed method is compared with those of the "conventional" SOM and an existing hybrid genetic algorithm. Relatively high accuracy and fast search speed have been achieved by using the proposed method.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.965-980
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• 2011

In this paper, the use of conditional Fuzzy C-Means (CFCM) aimed at estimation of desired states of an unknown digital communication channel is investigated for blind channel equalization. In the proposed CFCM, a collection of clustered centers is treated as a set of pre-defined desired channel states, and used to extract channel output states. By considering the combinations of the extracted channel output states, all possible sets of desired channel states are constructed. The set of desired states characterized by the maximal value of the Bayesian fitness function is subsequently selected for the next fuzzy clustering epoch. This modification of CFCM makes it possible to search for the optimal desired channel states of an unknown channel. Finally, given the desired channel states, the Bayesian equalizer is implemented to reconstruct transmitted symbols. In a series of simulations, binary signals are generated at random with Gaussian noise, and both linear and nonlinear channels are evaluated. The experimental studies demonstrate that the performance (being expressed in terms of accuracy and speed) of the proposed CFCM is superior to the performance of the existing method exploiting the "conventional" Fuzzy C-Means (FCM).

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.39-42
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• 1999

In this paper, a method based on the turbo principle is presented which combines diversity reception, equalization, and channel decoding, to combat the high transmission losses over the frequency-selective fading channel. The simulation results show that with the method presented, the BER performance within 0.3 ㏈ from that on the AWGN channel can be obtained over the frequency-selective fading channel in the investigated scenarios.