• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.10A
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• pp.1639-1644
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• 2001

Two decision feedback equalizer structures employing recurrent neural network (RNN) used for non-linear channels with severe intersymbol interference (ISI) and non-linear distortion are proposed in this paper, which skillfully put the traditional decision feedback structure for linear channels equalization into RNN, replace decision feedback signal with training signal in the learning process and adaptively adjust the learning step. Simulative results of the first type of two new equalizer structures have shown that it has better equalization performances than traditional recurrent neural network equalizer (RNNE) under the same condition.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.474-478
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• 1998

A new approach for the decision feedback equalizer(DFE) based on the back-propagation neural networks is described. We propose the method of optimal structure for back-propagation neural networks model. In order to construct an the optimal structure, we first prescribe the bounds of learning procedure, and the, we employ the method of incrementing the number of input neuron by utilizing the derivative of the error with respect to an hidden neuron weights. The structure is applied to the problem of adaptive equalization in the presence of inter symbol interference(ISI), additive white Gaussian noise. From the simulation results, it is observed that the performance of the propose neural networks based decision feedback equalizer outperforms the other two in terms of bit-error rate(BER) and attainable MSE level over a signal ratio and channel nonlinearities.

• Proceedings of the Optical Society of Korea Conference
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• 2000.02a
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• pp.56-57
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• 2000

In this paper, DFE with feedforward section(FDFE) is used to mitigate ISI and improve BER generated in the course of storage and retrieval of high-density 2-dimensional data in digital holographic memory system. From the result of experiment, BER performance of DFE with feedforward section is improved about 37% than binary-decision course by direct thresholding.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.4
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• pp.173-179
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• 2002

This paper describes an equalizer using the DFE (Decision Feedback Equalizer) structure, CMA (Constant Modulus Algorithm) and LMS (Least Mean Square) algorithms. The DFE structure has better channel adaptive performance and lower BER than the transversal structure. The proposed equalizer can be used for 16/64 QAM modems. We employ high speed multipliers, square logics and many CSAs (Carry Save Adder) for high speed operations. We have developed floating-point models and fixed-point models using the COSSAP$\^$TM/ CAD tool and developed VHDL filter. The proposed equalizer shows low BER in multipath fading channel. We have performed models. From the simulation results, we employ a 12 tap feedback filter and a 8 tap feedforward logic synthesis using the SYNOPSYS$\^$TM/ CAD tool and the SAMSUNG 0.5$\mu\textrm{m}$ standard cell library (STD80) and verified function and timing simulations. The total number of gates is about 130,000.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.7C
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• pp.704-711
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• 2002

This paper proposes a DFE (Decision Feedback Equalizer) equalizer ASIC using the Multi-Modulus Algorithm (MMA) for cable modem applications. We believe that it is the first effort to combine the DFE structure and the MMA algorithm. The proposed equalizer has been designed for 64/256 QAM modems. The existing MMA equalizer uses two transversal filters and updates two tap weights while the proposed equalizer uses two DFE filter banks to improve the channel adaptive performance and to reduce the number of taps and updates only one tap weights. We have used the 0.35 $\mu\textrm{m}$ standard cell library. The implemented equalizer ASIC operates at 8 MHz and provides 64 Mbps which is higher than existing equalizers. The total number of gates are about 160,000.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12A
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• pp.2015-2024
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• 1999

Presented in this paper are a new complex-umber filter architecture, which is suitable for an efficient implementation of baseband signal processing of digital communication systems, and a chip-set design of adaptive decision-feedback equalizer (ADFE) employing the proposed structure. The basic concept behind the approach proposed in this paper is to apply redundant binary (RB) arithmetic instead of conventional 2’s complement arithmetic in order to achieve an efficient realization of complex-number multiplication and accumulation. With the proposed way, an N-tap complex-number filter can be realized using 2N RB multipliers and 2N-2 RB adders, and each filter tap has its critical delay of $T_{m.RB}+T_{a.RB}$ (where $T_{m.RB}, T_{a.RB}$are delays of a RB multiplier and a RB adder, respectively), making the filter structure simple, as well as resulting in enhanced speed by means of reduced arithmetic operations. To demonstrate the proposed idea, a prototype ADFE chip-set, FFEM (Feed-Forward Equalizer Module) and DFEM (Decision-Feedback Equalizer Module) that can be cascaded to implement longer filter taps, has been designed. Each module is composed of two complex-number filter taps with their LMS coefficient update circuits, and contains about 26,000 gates. The chip-set was modeled and verified using COSSAP and VHDL, and synthesized using 0.8- μm SOG (Sea-Of-Gate) cell library.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.253-260
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• 2018

The acoustic communication channel in shallow underwater is typically shown as time-varying multipath fading channel characteristics. The received signal through channel transmission cause inter-symbol interference (ISI) owing to multiple components of different time delay and amplitude. To compensate for this, several techniques have been used, and one of them is acoustic equalizer. In this study, we used four equalizers - feed forward equalizer (FFE), decision directed equalizer (DDE), decision feedback equalizer (DFE) and combination DDE with DFE to compensate ISI. And we applied two adaptive algorithms to adjust coefficient of equalizers - normalized least mean square algorithm and recursive least square algorithm. As result, we found that it has a significant performance improvement over 6 dB on SNR in nonlinear equalizer. By combination of DFE and DDE has almost best performance in any case.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.103-108
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• 1998

The increase in the capacity of the digital magnetic recording systems inevitably causes severe intersymbol interference (ISI) and nonlinear distortions in the digital magnetic recording channel. In this paper, to cope with severe ISI and nonlinear distortions a neural decision feedback equalizer (NDFE) is applied to the digital magnetic recording channel - partial erasure channel model. In the performance comparison of bit error probability (or bit error ratio : BER) between the NDFE and the conventional decision feedback equalizer (DFE) via computer simulations. It has been found that as nonlinear distortions increase the NDFE has more SNR (SIgnal-to-Noise Ratio) advantage over the conventional DFE. In addition, in spite of the same recording density, as nonlinear distortions are increased, NDFE has the better performance of BER and the greater stability over conventional DFE.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.7
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• pp.1287-1294
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• 2006

In many current wireless packet data system, the short-burst transmissions are used, and training overhead is very significant for such short burst formats. So, the availability of the short training sequence and the fast converging algorithm is essential in the adaptive equalizer. In this paper, the new equalizer algorithm is proposed to improve the performance of a MTLMS (multiple-training least mean square) based DFE (decision feedback equalizer)using the short training sequence. In the proposed method, the output of the DFE is fed back to the LMS (least mean square) based adaptive DEF loop iteratively and used as an extended training sequence. Instead of the block operation using ML (maximum likelihood) estimator, the low-complexity adaptive LMS operation is used for overall processing. Simulation results show that the perfonnance of the proposed equalizer is improved with a linear computational increase as the iterations parameter in creases and can give the more robustness to the time-varying fading.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1706-1715
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• 1996

The decision feedback equalizer(DFE) received recent attention since it can compensate for channels with severe intersymbol interference(ISI) without as much noise enhancement as the linear equalizer(LE). In this paper, we propose a new DFE which can icrease the performance of DFE further by using error feedback. The performance increase is achieved by reducing correlation of error signal, which cannot be reduced by the feedforward or feedback filter. Hardware complexity for the proposed approcach is minimal since it requires only additional few taps to the conventional DFE. Based on theoretical analysis and computer simulations, the proposed approach is shown to be much more effective than the conventional DFE, especially for channels with large ISI.