• Journal of IKEEE
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• v.23 no.3
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• pp.934-940
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• 2019

In this paper, we propose a Reverse Differential Chaos Shift Keying (RE-DCSK) system for low cost, high reliability and high data rate non-coherent chaos communication .In RE-DCSK, reference signals are transmitted in the first slot as in the conventional differential chaos shift modulation scheme (DCSK) and in the second slot a time inversion block strengthens the autocorrelation of the chaos signal and uses the orthogonality of the two signals to obtain the information signal. RE-DCSK enables relatively double the data rate compared to DCSK and also improves the security of communications without any additional cost of system complexity.To prove its effectiveness, we analyze it through Rayleigh fading channel and additional white Gaussian noise (AWGN) channel based on the derived BER expression. The BER performance of the proposed system is improved when compared with the CDSK and DCSK system using AWGN channel.

• Journal of IKEEE
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• v.23 no.3
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• pp.800-804
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• 2019

This paper presents a dual-loop sub-sampling digital PLL for a 2.4 GHz IoT applications. The PLL initially performs a divider-based coarse lock and switches to a divider-less fine sub-sampling lock. It achieves a low in-band phase noise performance by enabling the use of a high resolution time-to-digital converter (TDC) and a digital-to-time converter (DTC) in a selected timing range. To remove the difference between the phase offsets of the coarse and fine loops, a phase offset calibration scheme is proposed. The phase offset of the fine loop is estimated during the coarse lock and reflected in the coarse lock process, resulting in a smooth transition to the fine lock with a stable fast settling. The proposed digital PLL is designed by SystemVerilog modeling and Verilog-HDL and fully verified with simulations.

• Journal of IKEEE
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• v.23 no.3
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• pp.805-810
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• 2019

We present a time-frequency analysis algorithm based on the multitaper method and the state-space frameworks. In general, time-frequency representations have a trade-off between the time duration and the spectral bandwidth by the uncertainty principle. To optimize the trade-off problems, the short-time Fourier transform and wavelet based algorithms have been developed. Alternatively, the authors proposed the state-space frameworks based on the multitaper method in the previous work. In this paper, we develop a real-time algorithm to estimate variances and spectrum using the state-space framework. We test our algorithm in spectral analysis of simulated data.

• Journal of IKEEE
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• v.24 no.4
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• pp.975-981
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• 2020

A 10 GHz LC voltage-controlled oscillator (VCO), which controls an amplitude of output signal, is proposed to improve the phase noise. The proposed amplitude control circuit for the LC VCO consists of a peak detector, an amplifier, and a current source. The peak detector is performed detecting the lowest voltage of the output signal by using two diode-connected NMOSFET and a capacitor. The proposed 10 GHz LC VCO with an amplitude control circuit for output signal is designed using a 55 nm CMOS process with a supply voltage of 1.2 V. Its area is 0.0785 ㎟. The amplitude control circuit used in the proposed LC VCO reduces the amplitude variation 242 mV generated in the output signal of the conventional LC VCO to 47 mV. Furthermore, it improves the peak-to-peak time jitter from 8.71 ps to 931 fs.

• The Journal of Korean Institute of Information Technology
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• v.17 no.4
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• pp.109-117
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• 2019

In modern society, due to various accidents and crime threats committed to an unspecified number of people, individual security awareness is increasing throughout society and various surveillance techniques are being actively studied. Still, there is a decline in robustness due to many problems, requiring higher reliability monitoring techniques. Thus, this paper suggests a real-time change detection technique to complement the low robustness problem in various environments and dynamic/static change detection and to solve the cost efficiency problem. We used the Self-Organizing Map (SOM) applied as a data clustering technique to implement change detection, and we were able to confirm the superiority of noise robustness and abnormal detection judgment compared to the detection technique applied to the existing image surveillance system through simulation in the indoor office environment.

• The Journal of Korean Institute of Information Technology
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• v.17 no.3
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• pp.43-50
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• 2019

In this paper, we propose a S-band oscillator with a reduced electrical size by applying a vertical split ring resonator(VSRR). The VSRR is a type of split ring resonator that operates as a resonator by the capacitance and inductance generated between the microstrip lines arranged on the top and bottom of the dielectric substrate and it has an advantage that the electrical size of the resonance circuit can be reduced as compared with the conventional ring resonator. In this paper, we design a VSRR operating over S-band and an oscillator using the VSRR as the resonant circuit. The proposed oscillator showed the output of 5.9dBm at 2.4HGz and showed the phase noise characteristics of -112.58dBc at 100KHz offset frequency and -117.85dBc at 1MHz offset.

• Journal of IKEEE
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• v.26 no.4
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• pp.568-576
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• 2022

Automatic modulation classification(AMC) is a core technique in Software Defined Radio(SDR) platform that enables smart and flexible spectrum sensing and access in a wide frequency band. In this study, we propose a simple yet accurate deep learning-based method that allows AMC for variable-size radio signals. To this end, we design a classification architecture consisting of two Convolutional Neural Network(CNN)-based models, namely main and small models, which were trained on radio signal datasets with two different signal sizes, respectively. Then, for a received signal input with an arbitrary length, modulation classification is performed by augmenting the input samples using a self-replicating padding technique to fit the input layer size of our model. Experiments using the RadioML 2018.01A dataset demonstrated that the proposed method provides higher accuracy than the existing methods in all signal-to-noise ratio(SNR) domains with less computation overhead.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.422-428
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• 2023

Ultrafast ultrasound imaging has been applied to various imaging approaches, including shear wave elastography, ultrafast Doppler, and super-resolution imaging. However, these methods are still challenging in real-time implementation for three Dimension (3D) or portable applications because of their massive data rate required. In this paper, we proposed an adaptive quantization method that effectively reduces the data rate of large Radio Frequency (RF) data. In soft tissue, ultrasound backscatter signals require a high dynamic range, and thus typical quantization used in the current systems uses the quantization level of 10 bits to 14 bits. To alleviate the quantization level to expand the application of ultrafast ultrasound imaging, this study proposed a depth-sectional quantization approach that reduces the quantization errors. For quantitative evaluation, Field II simulations, phantom experiments, and in vivo imaging were conducted and CNR, spatial resolution, and SSIM values were compared with the proposed method and fixed quantization method. We demonstrated that our proposed method is capable of effectively reducing the quantization level down to 3-bit while minimizing the image quality degradation.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.522-527
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• 2022

Object tracking is a field of signal processing that sequentially tracks the location of an object based on the previous-time location estimations and the present-time observation data. In this paper, we propose an adaptive scaling neural network that can track and adjust the scale of the input data with three recursive neural network (RNN) submodules. To evaluate object tracking performance, we compare the proposed system with the Kalman filter and the maximum likelihood object tracking scheme under an one-dimensional object movement model in which the object moves with piecewise constant acceleration. We show that the proposed scheme is generally better, in terms of root mean square error (RMSE) performance, than maximum likelihood scheme and Kalman filter and that the performance gaps grow with increased observation noise.

• Journal of IKEEE
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• v.28 no.2
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• pp.174-179
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• 2024

In this work, we introduce a complementary metal-oxide semiconductor(CMOS)-based integrated circuit(IC) measurement set-up for quantum computer control and read-out using a cryogenic refrigerator. CMOS circuits have to operate at extremely low temperatures of 3 to 5 K for qubit stability and noise reduction. The existing cryogenic measurement system is liquid helium quenching, which is expensive due to the long-term use of expendable resources. Therefore, we describe a cryogenic measurement system based on a closed cycle refrigerator (CCR) that is cost-free even when using helium gas for long periods of time. The refrigerator capable of reaching 4.7 K was built using a Gifford-Mcmahon(G-M) type cryocooler. This is expected to be a cryogenic refrigerator set-up with excellent price competitiveness.