• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.7
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• pp.332-334
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• 2006

In this paper, we present an equalization scheme for 8-VSB signals for the ATSC DTV system. We propose a complex feedback filter and complex feedback sample generator for DFE to equalize 8-VSB signals in order to efficiently remove multipath distortions causing leakages from the qudrature component. We show that the proposed structure outperforms the conventional DFE used for the digital VSB which uses a real-valued feedback filter with real-valued decisions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.753-758
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• 2011

The constant modulus algorithm (CMA) widely used in blind equalization applications minimizes the averaged power of constant modulus error (CME) defined as the difference between an instant output power and a constant modulus. In this paper, a decision feedback version of the linear blind algorithm based on maximization of the zero-error probability for CME is proposed. The Gaussian kernel of the maximum zero-error criterion is analyzed to have the property to cut out excessive CMEs that may be induced from severely distorted channel characteristics. Decision feedback approach to the maximum zero-error criterion for CME is developed based on the characteristic that the Gaussian kernel suppresses the outliers and this prevents error propagation to some extent. Compared to the linear algorithm based on maximum zero-error probability for CME in the simulation of blind equalization environments, the proposed decision feedback version has superior performance enhancement particularly in cases of severe channel distortions.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6B
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• pp.625-637
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• 2002

This study extends the modified linear feedback equalizer (MLFE), normally used for differentially coherent DPSK systems, to the equalization of double differentially coherent PSK (DDPSK) signals. By feeding back into the feedback part after modifying the equalizer output using decision feedback-based demodulation, the proposed equalizer can operate like an equalizer with a decision feedback structure. Simulation results showthat performances of the decision feedback demodulation-based feedback equalizer (DFD-FE) approach those of the DFE/coherent.

• Journal of Broadcast Engineering
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• v.10 no.4 s.29
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• pp.540-547
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• 2005

In the DFE(Decision Feedback Equalizer) for ATSC DTV receivers, there are decision errors in the slicer or. the simplified trellis decoder, and these decided false data comes to the feedback filter to make the error propagation phenomenon. The error propagation degrades the equalizer performance by increasing residual errors as well as slowing down the convergence rate. In this paper we propose a dual-feedback equalization structure. There are two feedback filters. One is the decision feedback filter which uses the simplified trellis decoder output data, the other is non-decision feedback filter which uses the equalizer output data. The additional non-decision feedback filter doesn't introduce the error propagation, so it can compensate the error propagation. The proposed structure accelerates the convergence rate as well as reduces output men-square error(MSE). We analyzed the performance enhancement of DTV receiver using dual-feedback equalization structure.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.12
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• pp.1408-1418
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• 2007

In this paper, we analyze the performance of pilot symbol assisted channel estimation and equalization schemes for OFDM systems over frequency-selective time-varying channels and propose methods to improve the system performance. In the least square(LS) and linear minimum mean square error(MMSE) channel estimation, time domain windowing is introduced for banding the frequency domain channel matrix. The linear MMSE and decision feedback equalization schemes are employed with the pilot symbols for channel estimation taken into account in the equalization process. To reduce computational complexity, the band LU matrix factorization algorithm is introduced in solving the linear systems involved in the equalization, and the performances are compared with the known previous results by computer simulations. When time domain windowing is employed in the decision feedback equalization, the matrix related with the decision feedback process is shown to be unhanded and the resultant performance degradation is analyzed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.343-347
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• 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.

• The Journal of the Acoustical Society of Korea
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• v.31 no.1
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• pp.1-10
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• 2012

The linear and decision-feedback equalization can mitigate time-varying intersymbol interference (ISI) caused by time-varying multipath propagation for underwater acoustic channels. The perfect elimination of interference components, however, is difficult using the linear equalization and the decision feedback equalizer has an error propagation problem. To overcome these shortcomings, this paper proposes an equalizer mode selection method using training sequences. The proposed method selects an equalization mode corresponding to the signal-to-noise ratio (SNR). If the SNR is low, the proposed system operates the linear equalizer for preventing the error propagation and if the SNR is high, the decision feedback equalizer for eliminating the residual ISI. Therefore, the proposed method can improve the error performance compared to the conventional equalizers. The computer simulation shows the proposed method improves the bit error performance using practical underwater channels responses acquired from the sea experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11A
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• pp.1167-1175
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• 2006

The ML-DFE(Maximum Likelihood-Decision Feedback Equalization) can be viewed as either a suboptimal signal detection method for reducing hardware complexity of ML or an enhanced detection method for reducing the effect of error propagation of SIC(Successive Interference Cancellation) in spatially multiplexed MIMO systems such as V-BLAST. The ML-DFE can achieve a higher diversity in rich scattering environments as well as reducing the error propagation effect by combing ML decoding with the DFE. In this paper, an MML-DFE(Modified Maximum Likelihood-Decision Feedback Equalization) is proposed to reduce the hardware complexity of the ML-DFE, without compromising performance. It is shown by FPGA implementation that the proposed MML-DFE can achieve the same performance as the ML-DFE with significantly reduced hardware complexity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.1 no.2
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• pp.199-207
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• 1997

The Maximum Likelihood Sequence Estimation scheme is modified to improve the error performance of the correlative coding in the Tamed FM. To remove intersymbol interference, the Decision Feedback Equalization scheme with the delayed LMS algorithm and the Viterbi algorithm(10-symbol delay) in the delayed adaptive equalization are proposed for the performance of decision-directed adaptive equalization under the High Frequency channels, and the condition of convergence is analyzed.