• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.5 no.3
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• pp.22-35
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• 1994

To improve the bandwidth efficiency in the environment of digital mobile communications, a correlative coded FM system is designed. The signal of this system has continuous phase and high power efficiency due to the constant envelope. But this signal also has a little loss of the SNR and some degradation of the BER. In this paper, a modified MLSE method which uses correlative coded signal is adopted to improve the performance of the receiver. The MLSE method improved the BER performance in the used channel. Without the decision feedback, the receiver performance was improved by 2dB and with it, by 4dB Particularly, the MLSE method and the decision feedback showed better performance in bad channels than in a stable telephone channel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.5
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• pp.413-423
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• 1991

Some digital partical response continuous phase modulation signals such as 3RC, 3SRC, 4SRC, and TFM have cconstant envelope characteristics and compact power spectra. However, their bit error rates in fast fading environments are too high when a simple frequency detection is used. This is due to high inter symbol interference resulting from adjacent bits. The improvement of BER performance by using DFE(Decision Feedback Equalization) to cancel the ISI of one adjacent bit is theoretically investigated in this paper. Numerical resuls are presentes to compare the BER performance of frequency detection with and without decision feedback equalization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10B
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• pp.1210-1215
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• 2011

In this paper, a supervised adaptive equalization algorithm based on probability density function (PDF) matching method is introduced and its decision-feedback version is proposed for underwater communication channels with strong impulsive noise and severe multipath characteristics. The conventional least mean square (LMS) algorithm based on mean squared error (MSE) criterion has shown to be incapable of coping with impulsive noise and multipath effects commonly shown in underwater communications. The linear PDF matching algorithm, which shows immunity to impulsive noise, however, has revealed to yield unsatisfying performance under severe multipath environments with impulsive noise. On the other hand, the proposed nonlinear PDF matching algorithm with decision feedback proves in the simulation to possess superior robustness against impulsive noise and multipath characteristics of underwater communication channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.247-252
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• 2015

Adaptive algorithms based on the criterion of zero-error probability (ZEP) have robustness to impulsive noise and their decision feedback (DF) versions are known to compensate effectively for severe multipath channel distortions. However the ZEP-DF algorithm computes several summation operations at each iteration time for each filter section and this plays an obstacle role in practical implementation. In this paper, the ZEP-DF with recursive gradient estimation (RGE) method is proposed and shown to reduce the computational burden of O(N) to a constant which is independent of the sample size N. Also the weight update of the initial state and the steady state is a continuous process without bringing about any propagation of gradient estimation error in DF structure.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.243-247
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• 2005

We propose an efficient block least-mean-square (BLMS) adaptive algorithm, in conjunction with error control coding, for direct-sequence code division multiple access (DS-CDMA) systems. The proposed adaptive receiver incorporates decision feedback detection and channel encoding in order to improve the performance of the standard LMS algorithm in convolutionally coded systems. The BLMS algorithm involves two modes of operation: (i) The training mode where an uncoded training sequence is used for initial filter tap-weights adaptation, and (ii) the decision-directed where the filter weights are adapted, using the BLMS algorithm, after decoding/encoding operation. It is shown that the proposed adaptive receiver structure is able to compensate for the signal-to­noise ratio (SNR) loss incurred due to the switching from uncoded training mode to coded decision-directed mode. Our results show that by using the proposed adaptive receiver (with decision feed­back block adaptation) one can achieve a much better performance than both the coded LMS with no decision feedback employed. The convergence behavior of the proposed BLMS receiver is simulated and compared to the standard LMS with and without channel coding. We also examine the steady-state bit-error rate (BER) performance of the proposed adaptive BLMS and standard LMS, both with convolutional coding, where we show that the former is more superior than the latter especially at large SNRs ($SNR\;\geq\;9\;dB$).

• Journal of Broadcast Engineering
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• v.8 no.4
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• pp.481-491
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• 2003

We present a near-optimal blind decision feedback equalizer (DFE) for Advanced Television Systems Committee digital television (DTV) receivers. By adopting a modified trellis decoder (MTD) with trace back depth of 1 for the decision device In the DFE, we obtain a hardware-efficient near-optimal blind DFE approaching to the optimal DFE which has no error propagation. The MTD uses absolute distance instead of Euclidean distance for computation of a path metric, resulting. In reduced computational complexity. Comparing to the conventional slicer, the MTD shows outstanding performance improvement of decision error probability and is comparable to the original trellis decoder using Euclidean distance. Reducing error propagation in the DFE leads to the improvement of convergence performance in terms of convergence speed and residual error. Simulation results show that the proposed blind DFE performs much better than the blind DFE with the slicer.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.65-68
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• 2000

It is well-known that the decision rule in the mini-mum mean-squares-error decision feedback equalizer(MMSE-DFE) is biased, and therefore suboptimum with respect to error probability. We present a new family of algorithms that solve the bias problem in the adaptive DFE. A novel constraint, called the constant-norm con-straint, is introduced unifying the quadratic constraint and the monic one. A new cost function based on the constant-norm constraint and Lagrange multiplier is defined. Minimizing the cost function gives birth to a new family of unbiased adaptive DFE. The simula-tion results demonstrate that the proposed method in-deed produce unbiased solution in the presence of noise while keeping very simple both in computation and im-plementation.

• 전자공학회논문지 IE
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• v.47 no.4
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• pp.39-47
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• 2010

This paper proposes a numerical analysis to prove that the performance of the differential phase detections (DPDs) with the decision feedback, such as the decision feedback DPD (DF-DPD) and the DPD with recursively generated phase reference (DPD-RGPR), approach the performance of the coherent detection with differential decoding. The conventional differential phase detection for M-ary DPSK can make the receiver architecture simple, while it can make the bit-error rate (BER) performance poor because of the previous noisy phase as a reference phase. To improve the BER performance of the conventional differential detection, multiple symbol differential detection methods, including DF-DPD and DPD-RGPR, have been proposed. However, the studies on the analysis and on the comparison of these methods have been little performed. Then, this paper mathematically intends to analyze and compare the performance of the DPDs with the decision feedback. The analysis results show that the DPDs with the decision feedback can have the performance equal to that of the coherent detection with differential decoding and be available for the noncoherent detection in the improved performance. Considering the hardware complexity, the DPD RGPR with the simple detection process by using the recursively generated phase reference can be more simply implemented than the DF-DPD based on the architecture whose complexity increases according to the increasing detection length.

• 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.

• Korean Business Review
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• v.3
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• pp.23-46
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• 1990

I. Introduction: In management control, business analysis has to do with a performance evaluation and is accounted much of manager's decision making, Business indicator accounting is the vehicle of decision making and also feedback can be accomplished by it. This study is to build up a logic about what capacity for use the business indicator accounting has in making decision. Therefore it is significant to make clear the adjustment of decision and to study the function of business indicator. II. Adjustment of Decision and Accounting Work: Adjustment of decision is connected with accounting now that business indicator accounting has a function of decision making. And it should be tied up with specialization as a structure of system, organization, communication and stage system. III. Adjustment of Decision and Managerial Accounting: Managerial account makes a great contributin to the management in which each adjustment of decision should be accomplished. Let me make mention of how the adjustment of decision is accomplished concretely, and what contribution che managerial accounting makes. In an adjustment of decision, centralization and decentrialization of enterprise are very import and I think the three problems, such as the extent of sphere (procurement, production and maketing), the face of affairs (planning, implementing and controlling), the final surge (decision making and action) can be accomplished by the business indicator accounting. IV. Structure of System and Disciplinary Approach for Decision: Decision can be classified into syncronized decision and continuous decision, and is closely connected with centralization and decentralization. In the course of systematizing, the sort of decision is classified into a man in charge of decision, and object of decision, conditions of decision, and an adjusting of decision. For it's object, it has an analogical thinking and an analytic subdivision about the target area. And it is premised on getting a scientific understanding. I think a disciplinary approach remains in solving these intricate problems. V. Conclusion: In this study I dealt with a specialization as a structure in management system and a theory that adjustment is a necessary process in decision making. For an adjustment of decision, exchanging informations and communication are necessary, and accounting is in charge of the process. And then the centralization and decentralization of decision should be connected in the way of adjustment of decision. In case of decentralization, the adjustment of decision is accomplished by the exchanging informations through feedback, and in case of centralization, by the all-round planning. And also I found that syncronized decision and decentralized decision are linked together. It is natural that the function of business indicator accounting is called for to render more services for it. Therefore, according to the extent of centralization and decentralization accounting to adjust the decision, can be various. Consequently, in relation to the structure of system. I think it is necessary to make a theoretical and empirical study of the business indicator accounting.