• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1354-1357
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• 2002

In this paper, we propose a suboptimal receiver combining adaptive array antenna and orthogonal decision-feedback detector in DS/CDMA system. Adaptive array antenna can cancel out undesired signal using beamforming scheme. However, if there are interfering signals from undesired users with the same incident angle as that of a desired user, an adaptive array antenna cannot suppress them. The proposed receiver can cancel out remaining interference from users having nearly the same beam pattern. And we employ Orthogonal Decision-Feedback Detector (ODFD) as multiuser detection. The ODFD performs as good as the decorrelating decision -feedback detector (DDD) with much less complexity. Simulation results show that the proposed system provides a significantly enhanced performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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• pp.2033-2035
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• 2007

This paper proposes a novel iterative LMS-based decision feedback equalizer for short burst transmission with relatively short training sequence. In the proposed equalizer, the longer concatenated training sequence can provide the more sufficient channel information and the reused original training sequence can provide the correct decision feedback information. In addition, the overall adaptive processing is performed using the low complexity LMS algorithm. The study shows the performance of the proposed method is enhanced with the number of iterations and, furthermore, better than that of the conventional LMS-based DFEs with the training sequence of longer or equal length. Computational complexity is increased linearly with the number of iterations.

• Journal of Communications and Networks
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• v.5 no.1
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• pp.7-18
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• 2003

In this paper, a decision feedback recurrent neural network equalizer and a modified real time recurrent learning algorithm are proposed, and an adaptive adjusting of the learning step is also brought forward. Then, a complex case is considered. A decision feedback complex recurrent neural network equalizer and a modified complex real time recurrent learning algorithm are proposed. Moreover, weights of decision feedback recurrent neural network equalizer under burst-interference conditions are analyzed, and two anti-burst-interference algorithms to prevent equalizer from out of working are presented, which are applied to both real and complex cases. The performance of the recurrent neural network equalizer is analyzed based on numerical results.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.11
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• pp.1237-1242
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• 2007

In this paper, we study STBC(Space Time Block Code) detection scheme in time varying Rayleigh fading channel. When the channel is varying during the time duration of STBC, the channel matrix of orthogonal STBC is not orthogonal. To get the optimum reception performance in this channel, joint ML detection scheme may be used, however this scheme requires high computation complexity. Decision feedback scheme is proposed to reduce the computation complexity with less reception performance. In this paper, we propose a novel STBC detection algorithm using double decision feedback which is less complex than the joint ML scheme and outperforms the conventional decision feedback scheme.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.9
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• pp.995-1004
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• 2010

In the channel-varying environment, it is very important to estimate the signal to noise ratio(SNR) of received signal and to transmit the signal effectively for the modern communication system. The performance of existing non-data-aided (NDA) SNR estimation methods are substantially degraded for high level modulation scheme such as M-ary APSK or QAM. In this paper, we propose a SNR estimation method which uses zero point auto-correlation of received signal per block and auto-/cross- correlation of decision feedback signal in OFDM system. Proposed method can be studied into two Types; Type 1 can estimate SNR by zero point auto-correlation of decision feedback signal based on the second moment property. Type 2 uses both zero point auto-correlation and cross-correlation based on the fourth moment property. In block-by-block reception of OFDM system, these two SNR estimation methods can be possible for the practical implementation due to correlation based the estimation method and they show more stable estimation performance than the previous SNR estimation methods. Also, we mathematically derive the SNR estimation expression according to computational difference of auto-/cross-correlation. Finally, Monte Carlo simulations are used to verify the proposed method.

• Asia pacific journal of information systems
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• v.5 no.1
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• pp.164-185
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• 1995

A considerable number of empirical studies have been conducted into the impact of graphical presentation of information on decision making performance. Very limited attention has been, however, devoted to the role of graphs as a means of delivering feedback. This paper investigated this issue by varying the presentation formats of outcome feedback in time series forecasting contexts. It was found that overall feedback was not decision-effective. Even enlarged and more salient feedback was of little value to overcome the conservative behavior. The results doubted the efficacy of graphical feedback in the design of EIS/DSS. Feedback did not appear to be a simple mechanism and further research is required to investigate its cognitive processes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.109-122
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• 2023

As platforms become primary decision making tools, platforms for decision have been introduced to improve quality of decision results. Because, decision platforms applied augmented decision-making process which uses experiences and feedback of users. This process creates a variety of alternatives tailored for users' abilities and characteristics. However, platform users choose alternatives before considering significant quality factors based on securing decision quality. In real world, platform managers use an algorithm that distorts appropriate alternatives for their commercial benefits. For improving quality of decision-making, preceding researches approach trying to increase rational decision -making ability based on experiences and feedback. In order to overcome bounded rationality, users interact with the machine to approach the optional situation. Differentiated from previous studies, our study focused more on characteristics of users while they use decision platforms. This study investigated the impact of quality factors on decision-making using platforms, the dimensions of systematic factors and user characteristics. Systematic factors such as platform reliability, data quality, and user characteristics such as user abilities and biases were selected, and measuring variables which trust, satisfaction, and loyalty of decision platforms were selected. Based on these quality factors, a structural equation research model was created. A survey was conducted with 391 participants using a 7-point Likert scale. The hypothesis that quality factors affect trust was proved to be valid through path analysis of the structural equation model. The key findings indicate that platform reliability, data quality, user abilities, and biases affect the trust, satisfaction and loyalty. Among the quality factors, group bias of users affects significantly trust of decision platforms. We suggest that quality factors of decision platform consist of experience-based and feedback-based decision-making with the platform's network effect. Through this study, the theories of decision-making are empirically tested and the academic scope of platform-based decision-making has been further developed.

• Journal of information and communication convergence engineering
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• v.4 no.2
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• pp.58-61
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• 2006

A key issue toward mobile multimedia communications is to create technologies for broadband signal transmission that can support high quality services. Such a broadband mobile communications system should be able to overcome severe distortion caused by timevarying multi-path fading channel, while providing high spectral efficiency and low power consumption. For these reasons, an adaptive suboptimum decision feedback equalizer (DFE) for the single-carrier shortburst transmissions system is considered as one of the feasible solutions. For the performance improvement of the system with the short-burst format including the short training sequence, in this paper, the multiple-training least mean square (MTLMS) based DFE scheme with soft decision feedback is proposed and its performance is investigated in mobile wireless channels throughout computer simulation.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1280-1285
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• 2017

In this paper, we consider iterative soft-decision feedback equalizers (sDFE), a.k.a. turbo equalizers for single-carrier transmission. Turbo equalizer takes log-likelihood ratio (LLR) feedback from channel decoder and convert the LLR into symbol estimates and variances to be used for the LLR update at the sDFE. Specifically, we consider both time domain and frequency-domain sDFE and compare their performances. The results shows that frequency-domain sDFE performs better than time-domain one and also that considerable gain can be obtained especially when the channel has deep nulls.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.8-25
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• 2017

This survey paper explores the application of multimodal feedback in automated systems for motor learning. In this paper, we review the findings shown in recent studies in this field using rehabilitation and various motor training scenarios as context. We discuss popular feedback delivery and sensing mechanisms for motion capture and processing in terms of requirements, benefits, and limitations. The selection of modalities is presented via our having reviewed the best-practice approaches for each modality relative to motor task complexity with example implementations in recent work. We summarize the advantages and disadvantages of several approaches for integrating modalities in terms of fusion and frequency of feedback during motor tasks. Finally, we review the limitations of perceptual bandwidth and provide an evaluation of the information transfer for each modality.