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​건국대학교 밀리미터파 집적시스템 연구실

밀리미터파 집적시스템 연구실에서는 아날로그, RF, 초고주파에 이르는 다양한 주파수 대역 IC기술과  전자기파 특성기반 다양한 응용 시스템 연구를 수행합니다.  모든 분들의 방문을 환영합니다.

위치: 공학관 321-1호 (교수 연구실), 신공학관 1117호 (학생 연구실)

NEWS & NOTICE

01.

23th RF/Analog Circuit Workshop

Best Paper Award

"Yoon, Joon-Hyuk"

Best LAB  "KU MISL"

02.

KIEES Summer Conf. 

Best Paper Award

"Son, Hyeon-Jin"

03.

2023 KIEES Radio & Wireless Comm. 

Best Paper Award

"Park, Joo-Eun"

OUR LATEST RESEARCHES

D-band CMOS Frequency Sixtupler using a Mode Analysis Technique

A miniaturized D-band frequency sixtupler using a mode analysis of the harmonics is proposed to improve the output power of the CMOS process using a low driving signal. The operation mode of the harmonics in a differential frequency multiplier is analyzed to independently control the behavior at odd- and even-order harmonics. The proposed CMOS sixtupler consists of a tripler, a buffer amplifier, a push–push doubler, and
impedance matching networks. The interstage network between the tripler and the buffer amplifier performs impedance matching of the desired frequency and filtering of unwanted signals. The network between the buffer and the doubler simultaneously performs impedance matching while acting as the harmonic reflector. The output power of the doubler located at the final stage of the sixtupler is improved by LC source degeneration, providing LC resonance, and a high impedance condition at
the second-harmonic frequency. The proposed sixtupler was implemented in an area of 0.4 mm2 using the 65-nm CMOS technology. The measurement results indicate a saturated power of −1.2 dBm with a harmonic rejection ratio (HRR) of 25 dBc for an input driving power of 15.5 dBm at 148.2 GHz. The maximum conversion gain (CG) is −0.7 dB at a low driving power of −6.5 dBm at 150.6 GHz.

Signal Preprocessing for Heartbeat Detection Using CW Doppler Radar

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A signal preprocessing method is proposed for effectively monitoring heartbeats from signals obtained using a continuous-wave (CW) Doppler radar. The proposed method consists of windowing with a size optimized for heartbeat detection, detrending to minimize the effect of dc drift, and data reconstruction to increase the fast Fourier transform (FFT) resolution. A window size of 3 s effectively extracts the heartbeat alone from the received signals of the CWradar, which comprised respiration, motion, and heartbeat signals. The effect of the low-frequency noise caused by the internal heat generation of hardware components is reduced by the detrending technique, and the low resolution of the FFT, due to a small number of samples, is improved through reconstruction by combining data from three windows. The signal-to-noise ratio of the measured waveform was improved to 5.83 dB using the proposed method in a 5.8-GHz CWradar. For the data acquired for 60 s, the proposed method showed a heartbeat detection accuracy of 95.8% by using a signal processing time 13% lower than that of the conventional method.

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