• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.3
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• pp.13-18
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• 2011

Sphere Decoding (SD) is a decoding technique able to achieve the Maximum Likelihood (ML) performance in fading environments; nevertheless, the main disadvantage of this technique is its high complexity, especially in poor channel conditions. In this paper, we present an adaptive hybrid algorithm which reduces the conventional Sphere Decoder's complexity and keeps the ML performance. The system called Adaptive OSIC-SD modifies its operation based on Signal to Noise Ratio (SNR) information and achieves an optimal performance in terms of Bit Error Rate (BER) and complexity. Through simulations, we probe that the proposed system maintains almost the same bit error rate performance of the conventional SD, and exhibits a lower, quasi-constant complexity.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.228-236
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• 2014

Towed array SONAR is deformed because it operates in fluid such as an ocean. It especially undergoes significant change in shape as a towing vessel takes a turn. In this case, beam pattern synthesis of the line array is limited, resulting in degradation in quality such as signal-to-noise ratio. This paper presents a modified two-step least squares algorithm based on the two-step least squares method. The shape of the sea-operated line array formation with the towing vessel changing course(angle) was modeled and the algorithm was subsequently applied. While changing course and location of the main lobe in beam pattern was altered, signal-to-noise ratio of steering beam pattern synthesis was analyzed by algorithm (proposed and others). As a result, the proposed algorithm presented improvement in performance by 2dB compared to other algorithms while forming relatively constant beam pattern.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.506-511
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• 2018

This paper proposes an GMM(Gaussian Mixture Model)-DNN(Deep Neural Network) hybrid-based feature compensation method for effective speech recognition in noisy environments. In the proposed algorithm, the posterior probability for the conventional GMM-based feature compensation method is calculated using DNN. The experimental results using the Aurora 2.0 framework and database demonstrate that the proposed GMM-DNN hybrid-based feature compensation method shows more effective in Known and Unknown noisy environments compared to the GMM-based method. In particular, the experiments of the Unknown environments show 9.13 % of relative improvement in the average of WER (Word Error Rate) and considerable improvements in lower SNR (Signal to Noise Ratio) conditions such as 0 and 5 dB SNR.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.5
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• pp.407-415
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• 2016

Recent wireless communication trends have emphasized the importance of energy-efficient transmission. In this paper, link adaptation with machine learning mechanism for maximum energy efficiency in multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) wireless system is considered. For reflecting frequency-selective MIMO-OFDM channels, two-dimensional capacity(2D-CAP) feature space is proposed. In addition, machine-learning-based bit and power adaptation(ML-BPA) algorithm that performs classification-based link adaptation is presented. Simulation results show that 2D-CAP feature space can represent channel conditions accurately and bring noticeable improvement in link adaptation performance. Compared with other feature spaces, including ordered postprocessing signal-to-noise ratio(ordSNR) feature space, 2D-CAP has distinguished advantages in either efficiency performance or computational complexity.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.5
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• pp.126-131
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• 2004

As a noninvasive imaging method, optical coherence tomography system has been extensively studied because it has some advantages such as imaging of high resolution, low cost, and compact size configuration. In order to improve the SNR of OCT system, two types of interferometers were configured and then, we compared simulation with measurement of reference sample. In the OCT system is configured with Michelson interferometer, the contrast of cross-sectional image is reduced with low SNR detection which is due to loss of feedback interference signal from light source part. Also, in order to image measured data with real time, image processing program is constructed. From results of simulation, it is confirmed that improved Michelson interferometer is improved about 10[dB] with a 50 : 50 fiber coupler. And from the measurement of reference sample, about 5[dB] is improved with a 50 : 50 fiber coupler. It is confirmed that the OCT system is configured with the improved Michelson interferometer which has a good distinctive cross-sectional image due to higher contrast.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.2
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• pp.189-195
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• 2013

In this paper, a land and maritime unified tourism information guide system is proposed which employs robust speech recognition in ship noise environments. Most of conventional front-ends for speech recognition have used a Wiener filter to compensate for stationary noise such as car or babble noises. However, such the conventional front-ends have limitation in reducing non-stationary noise that are occurred inside the ship on voyage. To overcome such a limitation, the proposed system incorporates nonlinear multi-band spectral subtraction to provide highly accurate tourism route recognition. It is shown from the experiment that compared to a conventional system the proposed system achieves relative improvement of a tourism route recognition rate by 5.54% under a noise condition of 10 dB signal-to-noise ratio (SNR).

• Journal of Advanced Navigation Technology
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• v.11 no.3
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• pp.274-280
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• 2007

An ultra-wideband signal is characterized by a radiated spectrum with wide bandwidth around a relatively low center frequency. In this paper, the bit error rate (BER), packet error rate (PER), and data throughput performance for an ultra-wideband system with M-ary correlation receiver are analyze in additive white Gaussian noise (AWGN) and co-channel interference channel. To evaluate the performance of UWB system, a set of UWB communication waveform as pulse position modulated (PPM) signals consisting of more than one UWB pulse is used. The M-ary PPM signals are defined to be equally correlated in order to simplify the system performance analysis. The analysis for system performance shows that the wireless channel error significantly degrades throughput performance and can be effectively increased by hybrid ARQ scheme. Also, an attempt for comparing the data throughput of ultra-wideband system on different performance improvement schemes and parameters has been made. From the performance evaluation process, it is shown that the effects of wireless channel and hybrid ARQ scheme for ultra wideband M-ary PPM system can be evaluated by means of a suitable combination of the PER, throughput vs. signal-to-noise power ratio per bit.

• Journal of Digital Contents Society
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• v.10 no.2
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• pp.189-198
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• 2009

In this paper, we propose a method to improve the performance of orthogonal frequency division multiplexing (OFDM) receivers by using oversampling the received signals. Demodulation of the received OFDM signals is to detect the amplitude and phase components of the subcarriers. From the oversampled OFDM signals, we can get redundant informations in frequency domain for the data, which are different in phase but the same in amplitude. By using these properties, we can obtain signal to noise ratio (SNR) gain by the oversampling ratio compared to the receivers which sampled with symbol rate. In this paper, we propose oversampled receivers whose oversampling ratio is expanded from integer to general rational number. Through computer simulations, we show the validity of the proposed methods by comparing the performance of the receivers with nonideal band-limiting filters.

• Atmosphere
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• v.34 no.1
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• pp.55-67
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• 2024

This paper aims to provide a detailed introduction to the concept of the Ratio of Predictable Component (RPC) and the Signal-to-Noise Paradox. Then, we derive insights from them by exploring the paradoxical features by conducting a seasonal and regional analysis through ensemble expansion in KMA's climate prediction system (GloSea). We also provide an explanation of the ensemble generation method, with a specific focus on stochastic physics. Through this study, we can provide the predictability limits of our forecasting system, and find way to enhance it. On a global scale, RPC reaches a value of 1 when the ensemble is expanded to a maximum of 56 members, underlining the significance of ensemble expansion in the climate prediction system. The feature indicating RPC paradoxically exceeding 1 becomes particularly evident in the winter North Atlantic and the summer North Pacific. In the Siberian Continent, predictability is notably low, persisting even as the ensemble size increases. This region, characterized by a low RPC, is considered challenging for making reliable predictions, highlighting the need for further improvement in the model and initialization processes related to land processes. In contrast, the tropical ocean demonstrates robust predictability while maintaining an RPC of 1. Through this study, we have brought to attention the limitations of potential predictability within the climate prediction system, emphasizing the necessity of leveraging predictable signals with high RPC values. We also underscore the importance of continuous efforts aimed at improving models and initializations to overcome these limitations.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.3
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• pp.282-291
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• 2011

Adaptive modulation(AM) is an important technique to increase the system efficiency, in which transmitter selects the most suitable modulation mode adaptively according to channel state in the temporary and spatially varying communication environment. Fixed modulation on channels with varying signal-to-noise ratio(SNR) is that the bit-errorrate(BER) probability performance is changing with the channel quality. An adaptive modulation scheme can be designed to have a BER which is constant for all channel SNRs. The correct as well as fast and simple SNR estimation is required essentially for this adaptive modulation. In order to operate adaptive modulation system effectively, in this paper, we analyze the effect of SNR estimation performance to it through the average BER and data throughput. Applying SNR estimation based on auto-correlation of decision feedback signal and others to adaptive modulation system, we also confirm performance degradation or improvement of its which is decided by SNR estimation error at each transition point of modulation level. Since SNR estimation based on auto-correlation of decision feedback signal shows stable estimation performance for various quadrature amplitude modulation(QAM) comparatively, this can be reduced degradation than others at each transition point of modulation level.