• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.524-532
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• 2002

This paper presents a new in-flight alignment method for an SDINS under large initial heading error. To handle large heading error, a new attitude error model is introduced. The attitude errors are divided into heading error and leveling errors using a newly defined horizontal frame. Some navigation error dynamic models are derived from the attitude error model for indirect feedback filtering of the in-flight alignment system. A Kalman filter with Position measurement is designed to estimate navigation errors as the indirect feedback filter Simulation results show that the proposed in-flight alignment method reduces the heading error very quickly from more than 40deg to about 5deg so as to apply a refined navigation filter. The total alignment process including leveling mode and navigation mode in addition to the proposed one allows large initial values not only in heading error but also in leveling errors.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.321-324
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• 1997

In this paper, Active Noise Control(ANC) algorithm is proposed based on the estimated frequency estimator of the reference signal. The conventional feedforward ANC algorithms should measure the reference and use it to calculate the gradient of the squared error and filter coefficients. For ANC systems applied to aircrafts and passenger ships, engines from which reference signal is usually measured is so far from seats where main part of controller is placed that the scheme might be difficult to implement or very costly. Feedback ANC algorithm which doesn't need to measure the reference uses the error signal to update the filter and is sensitive to unexpected transient noise like a sneeze, clapping of hands and so on The proposed algorithm estimates frequencies of the desired signal in real time using adaptive notch filter. New frequency estimation algorithm is proposed with the improved convergence rate, threshold SNR and computational simplicity. Reference is not measured but created with the estimated frequencies. It has strong similarity to the conventional feedback control because reference is made from error signal. Enhanced error signal is used to update the controller for better performance under the measurement noise and impact noise. The proposed ANC algorithm is compared with the conventional feedback control.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.1
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• pp.138-145
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• 2007

Wireless transmission system using the multipath channel is affected ISI due to the delay spread. So we use a decision feedback equalizer which consist of decision part and feedback filter for remove the ISI effectively. In this paper, we propose a improved adaptive decision feedback equalizer to mitigate ISI effectively. The proposed adaptive decision feedback equalizer is construct by using soft decision device and hierarchical feedback filter based on MMSE sub-optimal equalizer using the LMS algorithm. Soft decision device mitigate the error propagation in feedback filter by incorrectly detected decision symbol and feedback filter which is divided two step independently mitigate the ISI by using a adaptive algorithm. As a result this structure shows better performance than conventional decision feedback equalizer by mitigating the error propagation in filter cause incorrectly detecting symbol. and we get the MSE more rapidly by using larger step-size due to reduce the number of feedback filter tap. In computer simulation, we compare the bit error rate performance of proposed decision feedback equalizer with conventional one on the S-V channel model for UWB system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2601-2619
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• 2012

A differencing multiuser detection (MUD) method is proposed for multiple-input multiple-output (MIMO) direct sequence (DS) ultra-wideband (UWB) system to cope with the multiple access interference (MAI) and the computational efficiency in Nakagami fading channel. The method, which combines a multiuser-interference-cancellation-based decision feedback equalizer using error feedback filter (MIC DFE-EFF), a coefficient optimization algorithm (COA) and a differencing algorithm (DA), is termed as MIC DFE-EFF (COA) with DA for short. In the paper, the proposed MUD method is illuminated from the rudimental MIC DFE-EFF to the advanced MIC DFE-EFF (COA) with DA step by step. Firstly, the MIC DFE-EFF system performance is analyzed by minimum mean square error criterion. Secondly, the COA is investigated for optimization of each filter coefficient. Finally, the DA is introduced to reduce the computational complexity while sacrificing little performance. Simulations show a significant performance gain can be achieved by using the MIC DFE-EFF (COA) with DA detector. The proposed MIC DFE-EFF (COA) with DA improves both bit error rate performance and computational efficiency relative to DFE, DFE-EFF, parallel interference cancellation (PIC), MIC DFE-EFF and MIC DFE-EFF with DA, though it sacrifices little system performance, compared with MIC DFE-EFF (COA) without DA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.996-1007
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• 1996

In this paper, a blind adaptation method for a decision feedback equalizer (DFE) is proposed to deal with nominimum phase channels. This equalizer is composed of a linear transversal filter and a prediction error filter which are trained separately using constant modulus and decision feedback prediction algorithms, respectively, during the learnign time. The proposed algorithm guaranetees the DFE to converge to a suboptimal point on the condition that a linear transversal of the proposed scheme is illustrated and the performance is compared with conventional blind equlization algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.262-264
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• 2005

We propose a filter design method to suppress the effect of gyroscope mixed random errors at INS system level. It is based on the result that mixed random errors can be represented by a single equivalent ARMA model. At first step, the time difference of equivalent ARMA process is performed, which consider the characteristic of indirect feedback Kalman filter used in INS filter. Next, a state space conversion of time differenced ARMA model is achieved. If the order of AR is greater than that of MA, the controllable or observable canonical form is used. Otherwise, we introduce the state equation of which the state variable is composed of the ARMA model output and several step ahead predicts of that. At final step, a complete form state equation is presented. The simulation results shows that the proposed method gives less transient error and better convergence compared to the conventional filter which assume the mixed random errors as white noise.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.8 s.338
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• pp.17-24
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• 2005

This paper proposes a Decision Feedback Equalizer (DFT) with an error feedback filter for blind channel equalization. The proposed equalizer uses Least Mean Square(LMS) Algorithm and Multi-Modulus Algorithm (MMA), and has been designed for 64/256 QAM constellations. The existing MMA equalizer uses either two transversal filters or feedforward and feedback filers, while the proposed equalizer uses feedforward, feedback and error feedback filters to improve the channel adaptive performance and to reduce the number of taps. The proposed equalizer has been simulated using the $SPW^{TM}$ tool and it shows performance improvement. It has been modeled by VHDL and logic synthesis has been performed using the $0.25\;\mu m$ Faraday CMOS standard cell library. The total number of gates is about 190,000 gates. The proposed equalizer operates at 15 MHz. In addition, FPGA vertification has been performed using FPGA emulation board.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.56-61
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• 1998

The velocity measurement error in the velocity-aided SDINS on the maneuvering vehicle is unavoidable and degrades the performance of the SDINS. The characteristics of the velocity measurement error can be modeled as a random bias. This paper proposes a new method for estimating the velocity measurement error in the SDINS. The generalized likelihood ratio test is used for detecting the error and a modified separate-bias Kalman filter in the feedback configuration is suggested for estimating the magnitude of the velocity measurement error.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.279-285
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• 2003

In this paper we propose a blind decision feedback equalizer (DFE) that is characterized by the fact that it does not require channel estimation. Because the output of the optimized multistep prediction error filter (PEF) can be represented as a product of the channel partial impulse response and the transmitted sequence, a backward multistep PEF can be used as the blind DFE feedforward filter (FFF). The corresponding feedback filter (FBF) is obtained from the symbol -rate partial channel impulse response. The proposed algorithm has several advantages over existing blind channel estimation techniques, including stable performance without the necessity of exact channel order estimation.