• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9C
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• pp.876-881
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• 2006

In this paper, we propose a complex-valued IIR filter for digital VSB signals based on CMA in order to efficiently mitigate multipath distortions, especially the leakage from the quadrature component. The proposed equalizer overcomes the drawback of the conventional real-valued IIR equalizers that it attempts to equalize Hilbert transform of quadrature component. We demonstrate via simulation that the proposed complex IIR filter successfully mitigates the leakages from the quadrature component, while the conventional real IIR filter requires a longer IIR filter to achieve the same performance. We present cost function analysis for a simple two-tap case showing that the proposed IIR equalizer with CMA for VSB signals has a global minimum at the desired location.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3A
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• pp.328-336
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• 2006

A novel pre-equalization method for terrestrial DTV transmitters is presented. A pre-equalizer has been used in transmitters to correct group delay and amplitude distortions caused by a channel filter. In the proposed pre-equalizer, an equation-error adaptive IIR filtering scheme is adopted unlike the conventional pre-equalization using FIR filtering schemes. The pole-zero modelling property of IIR filters improves the signal-to-noise ratio and may deal with diverse linear distortions existing in DTV transmitters as well as the channel filter distortion. Simulation results show that the proposed IIR pre-equalizer performs better than the FIR pre-equalizer in terms of the residual mean-square error.

• ETRI Journal
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• v.31 no.2
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• pp.162-172
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• 2009

A linear-prediction-based blind equalization algorithm for single-input single-output (SISO) finite impulse response/infinite impulse response (FIR/IIR) channels is proposed. The new algorithm is based on second-order statistics, and it does not require channel order estimation. By oversampling the channel output, the SISO channel model is converted to a special single-input multiple-output (SIMO) model. Two forward linear predictors with consecutive prediction delays are applied to the subchannel outputs of the SIMO model. It is demonstrated that the partial parameters of the SIMO model can be estimated from the difference between the prediction errors when the length of the predictors is sufficiently large. The sufficient filter length for achieving the optimal prediction is also derived. Based on the estimated parameters, both batch and adaptive minimum-mean-square-error equalizers are developed. The performance of the proposed equalizers is evaluated by computer simulations and compared with existing algorithms.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.23-30
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• 1997

In this paper, a decision feedback recurrent neural equalization (DFRNE) scheme is proposed for adaptive equalization problems. The proposed equalizer models a nonlinear infinite impulse response (IIR) filter. The modified Real-Time recurrent Learning Algorithm (RTRL) is used to train the DFRNE. The DFRNE is applied to both linear channels with only intersymbol interference and nonlinear channels for digital video cassette recording (DVCR) system. And the performance of the DFRNE is compared to those of the conventional equalizaion schemes, such as a linear equalizer, a decision feedback equalizer, and neural equalizers based on multi-layer perceptron (MLP), in view of both bit error rate performance and mean squared error (MSE) convergence. It is shown that the DFRNE with a reasonable size not only gives improvement of compensating for the channel introduced distortions, but also makes the MSE converge fast and stable.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.8 s.350
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• pp.69-76
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• 2006

In this paper, we propose blind adaptation strategies for decision feedback equalizer (DFE) optimizing the operation mode between acquisitionand tracking modes based on adjustable soft decision devices. The proposed schemes select an optimal soft decision device to generate feedback samples for the DFE at a given noise to signal ratio, and apply corresponding adaptation rules which combine a blind infinite impulse response (IIR) filtering adaptation and the decision-directed least mean squared (DD-LMS) DFE adaptation. These adaptation approaches attempt to achieve not only smooth transition between acquisition and tracking of DFE but also mitigation of error propagation.