• Proceedings of the IEEK Conference
• /
• 2002.07c
• /
• pp.1901-1904
• /
• 2002

A good performance on communication systems is obtained by decreasing the length of training sequence In the initial stage of adaptive equalization. This paper presents a new approach to accomplish this, with the use of a training adaptive equalizer. The approach is based on combining the training and tracking modes, in which the training equalizer is updated by the LMS algorithm with the training sequence and then updated by a blind algorithm. By computer simulations, it is shown that a class of the proposed equalizers provides better performance than the conventional training equalizer.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.2A
• /
• pp.85-90
• /
• 2009

In this paper, as an alternative to constant modulus algorithm based on MSE, maximization of the probability that equalizer output power is equal to the constant modulus of the transmitted symbols is introduced. The proposed algorithm using the gradient ascent method to the maximum probability criterion has superior convergence and steady-state MSE performance, and the error samples of the proposed algorithm exhibit more concentrated density functions in blind equalization environments. Simulation results indicate that the proposed training has a potential advantage versus MSE training for the constant modulus approach to blind equalization.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38A no.10
• /
• pp.850-857
• /
• 2013

Turbo equalizer system is a method which can improve performance through a combination of the equalizer and decoder. The turbo equalizer has been mainly used a MAP equalizer. However, this turbo equalizer has a disadvantage that has a high computational complexity. To overcome the disadvantage and to improve efficiency of bandwidth, blind turbo equalization system is proposed. blind turbo equalization system has low equalization performance than conventional turbo equalization system. To circumvent this problem, we adapt the beamforming method based on the MUSIC algorithm. we confirmed that the proposed method improves the equalization performance.

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

• Journal of Internet Computing and Services
• /
• v.11 no.5
• /
• pp.19-26
• /
• 2010

The criterionmaximizing cross-correntropy (MCC) of two different random variables has yielded superior performance comparing to mean squared error criterion. In this paper we present a complex-valued blind equalizer algorithm for QAM and complex channel environments based on cross-correntropy criterion which uses, as two variables, equalizer output PDF and Parzen PDF estimate of a self-generated symbol set. Simulation results show significantly enhanced performance of symbol-point concentration with no phase rotation in complex-channel communication.

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.445-447
• /
• 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 the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.1
• /
• pp.121-127
• /
• 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 the Korea Academia-Industrial cooperation Society
• /
• v.13 no.1
• /
• pp.343-347
• /
• 2012

Non-linear equalization techniques using decision feedback structure are highly demanded for cancellation of intersymbol interferences occurred in severe channel environments. In this paper decision feedback structure is applied to the linear blind equalizer algorithm that is based on information theoretic learning and a randomly generated symbol set. At the decision feedback equalizer (DFE) the random symbols are generated to have the same probability density function (PDF) as that of the transmitted symbols. By minimizing difference between the PDF of blind DFE output and that of randomly generated symbols, the proposed DFE algorithm produces equalized output signal. From the simulation results, the proposed method has shown enhanced convergence and error performance compared to its linear counterpart.

• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.869-872
• /
• 2001

Blind identification and equalization of communication channel is important because it does not need training sequence, nor does it require a priori channel information. So, we can increase the bandwidth efficiency. The linear prediction error method is perhaps the most attractive in practice due to the insensitive to blind channel estimator and equalizer length mismatch as well as for its simple adaptive algorithms. In this paper, we propose method for fractionally spaced blind equalizer with arbitrary delay using one-step forward prediction error filter from second-order statistics of the received signals for SIMO channel. Our algorithm utilizes the forward prediction error as training sequences for data estimation and desired signal for channel estimation.

• Proceedings of the IEEK Conference
• /
• 2001.06a
• /
• pp.69-72
• /
• 2001

Blind equalization of transmission channel is important in communication areas and signal processing applications because it does not need training sequence, nor does it require a priori channel information. Recently, Tong et al. proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the second order statistics techniques, fur example, subspace method, prediction error method, and so on. The linear prediction error method is perhaps the most attractive in practice due to the insensitive to blind equalizer length mismatch as well as for its simple adaptive filter implementation. Unfortunately, the previous one-step prediction error method is known to be limited in arbitrary delay. In this paper, we induce the optimal delay, and propose the adaptive blind equalizer with multi-step linear prediction using RLS-type algorithm. Simulation results are presented to demonstrate the proposed algorithm and to compare it with existing algorithms.