• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.578-585
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• 2011

Nowadays, wireless local area networks are widely deployed so that stations can potentially associate with an access point. The AP selection strategy is one of the significant research areas for wireless local area networks. The selection strategy solves the relevant problem is which AP can be selected and associated with a station so that the efficient resource utilization can be obtained. Rather than merely choosing the AP with the strongest received signal strength, however, we calculate effective throughput for each neighboring AP and use it as a basis for AP selection. Referencing the throughput is better than referencing the signal strength only because the network may contain a severe load imbalance. We have performed computer simulations using OPNET modeler in order to verify the performance of the proposed scheme. The results show us that the proposed selection method outperforms that of the conventional one in terms of throughput and delay.

• The Journal of the Acoustical Society of Korea
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• v.30 no.8
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• pp.461-467
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• 2011

Accurate classification of input signals is the key prerequisite for variable bit-rate coding, which has been introduced in order to effectively utilize limited communication bandwidth. Especially, recent surge of multimedia services elevate the importance of speech/music classification. Among many speech/music classifier, the ones based on support vector machine (SVM) have a strong selling point, high classification accuracy, but their computational complexity and memory requirement hinder their way into actual implementations. Therefore, techniques that reduce the computational complexity and the memory requirement is inevitable, particularly for embedded systems. We first analyze implementation of an SVM-based classifier on embedded systems in terms of execution time and energy consumption, and then propose two techniques that alleviate the implementation requirements: One is a technique that removes support vectors that have insignificant contribution to the final classification, and the other is to skip processing some of input signals by virtue of strong correlations in speech/music frames. These are post-processing techniques that can work with any other optimization techniques applied during the training phase of SVM. With experiments, we validate the proposed algorithms from the perspectives of classification accuracy, execution time, and energy consumption.

• Journal of Korea Multimedia Society
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• v.10 no.8
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• pp.958-966
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• 2007

In this paper, we implement a sound-enhanced MPEG-1 audio decoder on embedded OS Platform. Low bit rate lossy audio codecs such as MP3, OGG, and AAC for mitigating the problems in storage space and network bandwidth suffer a major common problem such as a loss of high frequency fidelity of audio signal. This high frequency loss will reproduce only a band-limited low-frequency part of audio in the standard CD-quality audio. In order to overcome this problem, we embedded a sound enhancement algorithm into the MPEG-1 audio decoder and then the algorithms optimized according to the characteristic of the MPEG-1 audio layer I, II, III were implemented on an embedded OS platform. From the experimental results with spectrum analysis and listening test, we confirm the superiority of the proposed system compared to the standard MPEG-1 audio decoder.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.9
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• pp.519-527
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• 2014

Adaptive arrays can minimize contributions from interferences incident onto an sensor array while preserving a signal the direction vector of which corresponds to the array steering vector to within a scalar factor. If there exist errors in the steering vector, severe performance degradation can be caused since the desired signal is misunderstood as an interference by the array. This paper presents an adaptive beamforming method which is robust against steering vector errors, exploiting a range of the desired signal direction. In the presented method, an correlation matrix of array response vectors is obtained through integration over the direction range and a minimization problem is formulated using some eigenvectors of the correlation matrix such that a more accurate steering vector than initially given one can be found. The minimization problem is transformed into a relaxed SDP (semidefinite program) problem, which can be effectively solved since it is a sort of convex optimization. Simulation results show that the proposed method outperforms existing ones such as ORM (outside-range-based method) and USM (uncertainty-based method).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.101-108
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• 2013

In this paper, we propose a method in which the negative acknowledge (NACK) message is used as command for cooperation and spectrum sharing. This allows for an automatic request for cooperation and sharing when the direct link of the primary user is in outage, and also allows for saving the number of control messages in cooperation-spectrum sharing based paradigm. In the sharing phase, the selected relay shares a power fraction of $1-{\alpha}$ for secondary transmitted signal while the remaining of ${\alpha}$ is for primary retransmitted signal. In the case of no relay collected, primary transmitter uses NACK as a command to retransmit the signal with fully power fraction (${\alpha}=1$). Both systems are assumed to employ BPSK signals. In this scheme, we propose the joint optimal decoding in the secondary user. The frame error rate (FER) performance at both systems is then analyzed. The theoretical and simulation results validate the analysis and confirm the efficiency of the protocol.

• Journal of IKEEE
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• v.2 no.1 s.2
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• pp.34-41
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• 1998

An integrated circuit for magnetic stripe storage system is implemented. All the analog and digital circuits are integrated in one chip. The analog block contains preamplifier, peak detecter, comparator and reference generater. And digital block includes reference window signal generater, up/down counter for F/2F signal measurement, bit-error detection logic, and control logic. Both the encoding and decoding functions for F/2F signal processing are provided. An AGC(automatic gain control) circuit which was included in conventional circuits is eliminated due to optimized circuit design. Misreading prevention circuits are also proposed by fixing up new reference bit when broken bits are detected. The prototype chip is implemented using $0.8{\mu}m$ N-well CMOS technology and operates from 3.3 V to 7.5 V of supply voltage. It occupies a die area of $3.04mm^2(1.6mm{\times}1.9mm)$ and dissipates 8 mW with a 5 V supply voltage.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.7
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• pp.620-624
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• 2016

In this paper we designed a current mode logic frequency divider to transmit a baseband amplitude modulated signal. From simulation result, we studied input and output waveforms according to the variation of input bias voltage. For the purpose of the verification of the study, we designed a current mode logic frequency divider at 1,400 MHz. The designed frequency divider operates between 100 MHz and 3,000 MHz, for -33 dBm input power. The circuit draws $I_{total}=30mA$ from $V_{DD}=3V$ supply, and the simulation result shows that an amplitude modulated signal at 1,400 MHz with the modulation index of 0.5 was successfully downconverted to 700 MHz.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.53-59
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• 2009

Integrating a field of transportation and IT is becoming a novel solution to social and economic problems which was previously focused on the investment in infrastructures. It also created new areas of industry such as ITS and telematics. Especially, vehicle communication is being considered very important and DSRC is also important in the field of rational ITS in recent. DSRC OBE has come into wide use through ETCS. In the field of traffic signal control, the research to implement an optimal traffic signal control system using a real-time information of good quality is being carried out and also the study of WISDOM was successfully completed. This paper shows the development of Dynamic-Dilemma zone warning service utilizing WISDOM and the evaluation of a reliability and a practicality through the field test. While the proposed Dynamic-Dilemma warning system transmits an information of signal time optimized by WISDOM, the OBE which receives this information makes dilemma zone based on its location and speed and gives warning to a driver.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.3
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• pp.37-46
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• 2012

In RADAR and SONAR detection systems, noise environment can be classified into homogeneous and heterogeneous environment. Especially heterogeneous environments are modelled as target masking and clutter edge. Since the variability-index (VI) CFAR, a composed CFAR algorithm, dynamically selects one of the mean-level algorithms based on the VI and the MR (mean ratio) test, it is robust to various environments. However, the VI CFAR still suffers from lowered detection probabilities in heterogeneous environments. To overcome these problems, we propose an improved VI CFAR processor where TM (trimmed mean) CFAR and a sub-windowing technique are introduced to minimize the degradation of the detection probabilities appeared in heterogeneous environments. Computer simulation results show that the proposed method has the better performance in terms of detection probability and false alarm probability compared to the VI CFAR and single CFAR algorithms.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.261-268
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• 2020

Machine learning is achieved by making a cost function from a given digital signal data and optimizing the cost function. The cost function here has local minimums in the cost function depending on the amount of digital signal data and the structure of the neural network. These local minimums make a problem that prevents learning. Among the many ways of solving these methods, our proposed method is to change the learning step-size. Unlike existed methods using the learning rate (step-size) as a fixed constant, the use of multivariate function as the cost function prevent unnecessary machine learning and find the best way to the minimum value. Numerical experiments show that the results of the proposed method improve about 3%(88.8%→91.5%) performance using the proposed method rather than the existed methods.