• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.200-220
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• 2016

Orthogonal frequency division multiplexing (OFDM) signals suffer from the problem of large peak-to-average power ratio (PAPR) which complicates the design of the analog front-end of the system. Companding is a well-known PAPR reduction technique that reduces the PAPR by transforming the signal amplitude using a deterministic function. In this paper, a novel piecewise linear companding transform is proposed. The design criteria for the proposed transform is developed by investigating the relationships between the compander and decompander's profile and parameters with the system's performance metrics. Using analysis and simulations, we relate the companding parameters with the bit error rate (BER), out-of-band interference (OBI), amount of companding noise, computational complexity and average power. Based on a set of criteria developed thereof, we formulate the design of the proposed transform. The main aim is to preserve the signal's attributes as much as possible for a predetermined amount of PAPR reduction. Simulations are carried out to evaluate and compare the proposed scheme with the existing companding transforms to demonstrate the enhancement in PAPR, BER and OBI performances.

• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.197-207
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• 2006

When the latency of a flow in a fair packet scheduler, which is determined by its rate, violates its required delay bound, the scheduler should reduce the latency with even raising the rate being reserved for the flow. The excessively reserved rate win enforce some outgoing link bandwidth be lost. This loss can not be, unfortunately, evaluated by the three metrics of latency, fairness and implementation complexity used in previous works. This paper is aimed to first introduce the metric of bandwidth utilization to investigate the bandwidth loss in a scheduler and then evaluate the timestamp based schedulers in terms of the bandwidth and payload utilizations. The results show that the bandwidth utilization increases with loosing the required delay bound and, in particular, schedulers with the latency property of WFQ have much better payload utilization by up to 50% than that in the SCFQ one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1257-1265
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• 2015

In this paper, we describe a greedy user selection scheme for multiuser multiple-input multiple-output (MIMO) systems. We propose a new metric which has significantly improved performance compared to the Frobenius norm metric. The approximation of projection matrix is applied to increase the accuracy of Frobenius norm of effective channel matrix. We analyze the computational complexity of two metrics by using flop counts, and also verify the achievable sum rate through numerical simulation. Our simulation result shows that the proposed metric can achieve the improved sum rate as the number of user antenna increases.

• ETRI Journal
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• v.26 no.2
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• pp.101-111
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• 2004

This paper presents a near-optimum blind decision feedback equalizer (DFE) for the receivers of Advanced Television Systems Committee (ATSC) digital television. By adopting a modified trellis decoder (MTD) with a trace- back depth of 1 for the decision device in the DFE, we obtain a hardware-efficient, blind DFE approaching the performance of an optimum DFE which has no error propagation. In the MTD, the absolute distance is used rather than the squared Euclidean distance for the computation of the branch metrics. This results in a reduction of the computational complexity over the original trellis decoding scheme. Compared to the conventional slicer, the MTD shows an outstanding performance improvement in decision error probability and is comparable to the original trellis decoder using the Euclidean distance. Reducing error propagation by use of the MTD 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, and the difference is prominent at the trellis decoder following the blind DFE.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.12
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• pp.28-33
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• 2007

We present a space-time trellis coded OFDM system in flow fading channels. Generalized principal ratio combining (GPRC) is also analyzed theoretically in frequency domain. The analysis show that the decoding metric of GPRC include the metrics of maximum likelihood (ML) and PRC. The computer simulations with M-PSK modulation are obtained in frequency flat and frequency selective lading channels. The decoding complexity and simulation running times are also evaluated among the decoding schemes.

• Korean Journal of Remote Sensing
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• v.20 no.1
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• pp.57-64
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• 2004

In GIS-based network analysis, topological measure of network structure can be considered as one of important factors in the urban transportation analysis. Related to this measure, it is known that the connectivity indices such as alpha index and gamma index, which mean degree of network connectivity and complexity on a graph or a circuit, provide fundamental information. On the other hand, shimbel index is one of GIS-based spatial metrics to characterize degree of network concentration. However, the approach using these quantitative indices has not been widely used in practical level yet. In this study, an application program, in complied as extension, running on ArcView- GIS is implemented and demonstrated case examples using basic layers such as road centerline and administrative boundary. In this approach, geo-spatial imagery can be effectively used to actual applications to determine the analysis zone, which is composed of networks to extract these indices. As the results of the implementation and the case examples, it is notified that alpha and gamma indices as well as shimbel index can be used as referential data or auxiliary information for urban planning and transportation planning.

• ETRI Journal
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• v.41 no.5
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• pp.626-636
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• 2019

A novel algorithm for joint user selection and optimal power allocation for Stackelberg game-based revenue maximization in a downlink non-orthogonal multiple access (NOMA) network is proposed in this study. The condition for the existence of optimal solution is derived by assuming perfect channel state information (CSI) at the transmitter. The Lagrange multiplier method is used to convert the revenue maximization problem into a set of quadratic equations that are reduced to a regular chain of expressions. The optimal solution is obtained via a univariate iterative procedure. A simple algorithm for joint optimal user selection and power calculation is presented and exhibits extremely low complexity. Furthermore, an outage analysis is presented to evaluate the performance degradation when perfect CSI is not available. The simulation results indicate that at 5-dB signal-to-noise ratio (SNR), revenue of the base station improves by at least 15.2% for the proposed algorithm when compared to suboptimal schemes. Other performance metrics of NOMA, such as individual user-rates, fairness index, and outage probability, approach near-optimal values at moderate to high SNRs.

• Journal of Information Science Theory and Practice
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• v.9 no.4
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• pp.15-34
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• 2021

Text clustering is one of the most commonly used methods for detecting themes or types of documents. Text clustering is used in many fields, but its effectiveness is still not sufficient to be used for the understanding of Arabic text, especially with respect to terms extraction, unsupervised feature selection, and clustering algorithms. In most cases, terms extraction focuses on nouns. Clustering simplifies the understanding of an Arabic text like the text of the Quran; it is important not only for Muslims but for all people who want to know more about Islam. This paper discusses the complexity and limitations of Arabic text clustering in the Quran based on their themes. Unsupervised feature selection does not consider the relationships between the selected features. One weakness of clustering algorithms is that the selection of the optimal initial centroid still depends on chances and manual settings. Consequently, this paper reviews literature about the three major stages of Arabic clustering: terms extraction, unsupervised feature selection, and clustering. Six experiments were conducted to demonstrate previously un-discussed problems related to the metrics used for feature selection and clustering. Suggestions to improve clustering of the Quran based on themes are presented and discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.249-251
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• 2021

PBFT (Practical Byzantine Fault Tolerant) is a consensus algorithm that guarantees higher processing speed compared to PoW (Proof of Work) and absolute finality that records are not overturned due to the superiority of computing power. However, due to the complexity of the message, there is a limit that the network load increases exponentially as the number of participating nodes increases. PBFT is an important factor in determining the performance of a blockchain network, but studies on evaluation metrics and evaluation technologies are lacking. In this paper, we propose a PBFT evaluation framework that is convenient to change the consensus algorithm to easily evaluate quantitative indicators and improved methods for evaluating PBFT.

• Annual Conference of KIPS
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• 2023.11a
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• pp.30-33
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• 2023

The recent scholarly focus has been directed towards the expeditious and accurate detection of salient objects, a task that poses considerable challenges for resource-limited edge devices due to the high computational demands of existing models. To mitigate this issue, some contemporary research has favored inference speed at the expense of accuracy. In an effort to reconcile the intrinsic trade-off between accuracy and computational efficiency, we present novel model for salient object detection. Our model incorporate group-wise attentive module within the decoder of the encoder-decoder framework, with the aim of minimizing computational overhead while preserving detection accuracy. Additionally, the proposed architectural design employs attention mechanisms to generate boundary information and semantic features pertinent to the salient objects. Through various experimentation across five distinct datasets, we have empirically substantiated that our proposed models achieve performance metrics comparable to those of computationally intensive state-of-the-art models, yet with a marked reduction in computational complexity.