• 한국전자파학회논문지
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• 제21권3호
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• pp.321-330
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• 2010

본 논문에서는 컴프레시브 RFID 신호를 탐지하기 위한 컴프레시브 수신기의 이론적 배경과 구체적 구현 방법, 그리고 분산 지연선과 chirp LO의 설계 방안에 대해 기술하였다. 컴프레시브 수신기의 주요 구성품 중 하나인 분산 지연선을 대역폭 6 MHz, 분산 지연 시간 $13{\mu}s$으로 설계하여 $LiNbO_3$ 재질 기반의 SAW(Surface Acoustic Wave) 기술을 통해 구현하였고, DDS(Direct Digital Synthesizer)를 이용하여 chirp LO를 구현하였다. 또한 RFID 리더에 내장되어 연동될 수 있도록 컴프레시브 수신기를 구성하였다. 시험 결과, 단일 신호 입력시 주파수 오차는 최대 25 kHz, 수신 감도는 -44 dBm, 500 kHz 간격으로 동시에 입력되는 6개의 신호에 대한 주파수 오차는 최대 75 kHz로서 제작된 컴프레시브 수신기가 밀집된 RFID 운영 환경에 적합함을 보였다.

• 한국전자파학회논문지
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• 제21권5호
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• pp.501-509
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• 2010

본 논문에서는 컴프레시브 수신기가 내장된 RFID 리더의 주파수 충돌 회피 성능을 분석하였다. 다수의 밀집 리더가 동시에 운영되는 환경에서 기존 RFID 리더의 인식률과 컴프레시브 수신기가 적용된 우리가 제안하는 RFID 리더의 인식률을 측정하였다. 시험 결과 제안된 RFID 리더의 인식률은 기존 리더에 비해 2.7배 정도 개선되었고, 특히 제안된 리더들로만 운영되는 환경에서는 인식률의 저하가 거의 나타나지 않았다.

• 한국전자파학회논문지
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• 제20권11호
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• pp.1186-1193
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• 2009

본 논문에서는 컴프레시브 수신기용 chirp LO의 새로운 구현 방안으로 DDS 방식을 사용하였고, 이를 UHF 대역 RFID 신호를 탐지하기 위한 컴프레시브 수신기에 적용하였다. 수신기의 입력 주파수는 908.5~914 MHz, DDL 대역폭은 6 MHz, 분산지연 시간은 $13\;{\mu}s$으로 설계하였다. 또한 완전한 압축 메커니즘을 위해 DDS 기반의 chirp LO 주파수 대역폭은 12 MHz, 스윕 시간은 $26\;{\mu}s$으로 설계하였다. 제작된 컴프레시브 수신기 압축 펄스의 3 dB 폭은 260 ns으로 측정되었고, 동시 입력 신호들에 대해 주파수 분해능은 200 kHz 이하로서 제시된 DDS 기반의 chirp LO와 컴프레시브 수신기가 UHF 대역 RFID 신호 탐지에 적합함을 보였다.

• Journal of electromagnetic engineering and science
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• 제6권2호
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• pp.110-116
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• 2006

A reflective array type surface acoustic wave(SAW) dispersive delay line(DDL) with high time-bandwidth at the V/UHF-band is designed and fabricated for compressive receiver applications. This type of the SAW DDL has the properties of the relative bandwidth of 20 %, the time delay of 49.89 usec, the insertion loss of 38.5 dB and the side lobe rejection of 39 dB. In comparison with a commercial SAW DDL, the insertion loss, amplitude ripple and side lobe rejection are improved by $1.5dB{\pm}0.6dB$ and 4 dB respectively. Using the fabricated SAW DDL, the prototype of the compressive receiver is developed. It is composed of RF converter, fast tunable LO, chirp LO, A/D converter, signal processing unit and control unit. This prototype system shows a fine frequency resolution of below 30 kHz with high scan rate.

• 한국군사과학기술학회지
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• 제21권4호
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• pp.437-446
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• 2018

This paper describes the real-time logic implementation of orthogonal matching pursuit(OMP) algorithm for compressive sensing digital receiver. OMP contains various complex-valued linear algebra operations, such as matrix multiplication and matrix inversion, in an iterative manner. Xilinx Vivado high-level synthesis(HLS) is introduced to design the digital logic more efficiently. The real-time signal processing is realized by applying dataflow architecture allowing functions and loops to execute concurrently. Compared with the prior works, the proposed design requires 2.5 times more DSP resources, but 10 times less signal reconstruction time of $1.024{\mu}s$ with a vector of length 48 with 2 non-zero elements.

• Smart Structures and Systems
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• 제20권1호
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• pp.35-42
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• 2017

Recently, compressive sensing based data loss recovery techniques have become popular for Structural Health Monitoring (SHM) applications. These techniques involve an encoding process which is onerous to sensor node because of random sensing matrices used in compressive sensing. In this paper, we are presenting a model where the sampled raw acceleration data is directly transmitted to base station/receiver without performing any type of encoding at transmitter. The received incomplete acceleration data after data losses can be reconstructed faithfully using compressive sensing based reconstruction techniques. An in-depth simulated analysis is presented on how random losses and continuous losses affects the reconstruction of acceleration signals (obtained from a real bridge). Along with performance analysis for different simulated data losses (from 10 to 50%), advantages of performing interleaving before transmission are also presented.

• Smart Structures and Systems
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• 제22권2호
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• pp.231-237
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• 2018

A significant data problem is encountered with condition monitoring because the sensors need to measure vibration data at a continuous and sometimes high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate their efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer data than traditional data sampling methods. This sensing paradigm is applied to condition monitoring with an improved machine learning algorithm in this study. For the experiments, a built-in rotating system was used, and all data were compressively sampled to obtain compressed data. The optimal signal features were then selected without the signal reconstruction process. For damage classification, we used the Variance Considered Machine, utilizing only the compressed data. The experimental results show that the proposed compressive sensing method could effectively improve the data processing speed and the accuracy of condition monitoring of rotating systems.

• Journal of Information Processing Systems
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• 제11권3호
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• pp.342-353
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• 2015

It is widely accepted that single carrier frequency division multiple access (SC-FDMA) is an excellent candidate for broadband wireless systems. Channel estimation is one of the key challenges in SC-FDMA, since accurate channel estimation can significantly improve equalization at the receiver and, consequently, enhance the communication performances. In this paper, we study the application of compressive sensing for sparse channel estimation in a SC-FDMA system. By skillfully designing pilots, their patterns, and taking advantages of the sparsity of the channel impulse response, the proposed system realizes channel estimation at a low cost. Simulation results show that it can achieve significantly improved performance in a frequency selective fading sparse channel with fewer pilots.

• 한국소음진동공학회논문집
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• 제26권6_spc호
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• pp.651-659
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• 2016

Condition monitoring (CM) encounters a large data problem due to sensors that measure vibration data with a continuous, and sometimes, high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate the efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer samples compared to traditional sampling methods. For the experiments a built-in rotating system was used and all data were compressively sampled to obtain compressed data. Optimal signal features were then selected without the reconstruction process and were used to detect and classify damage. The experimental results show that the proposed method could improve the data processing speed and the accuracy of condition monitoring of rotating systems.

• 한국전자파학회논문지
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• 제23권7호
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• pp.797-804
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• 2012

본 논문은 저전력 통신을 위하여, 압축 센싱에 적용한 QAPM 변조 방식을 제안한다. QAPM 변조 방식은 QAM 변조 방식과 PPM 변조 방식을 결합한 방식으로써, 자리(PPM의 posion) 개수가 늘어날수록 심볼 간의 거리가 멀어져 BER 성능과 전력 효율을 향상시킨다. 또한, 자리개수를 늘릴수록 대역이 손실 발생될 수 있으나, 성김(sparsity) 특성은 증가된다. 이러한 높은 성김 특성은 Nyquist 속도 이하의 샘플링으로도 완전하게 신호를 복원할 수 있는 압축 센싱에 적용하기에 매우 적합하다. 따라서 본 논문은 압축 센싱에 적용된 QAPM 시스템이 수신기에 있는 ADC(Analog Digital Converter)의 부담을 줄이면서도 BER 성능을 향상시키는 저전력 시스템임을 시뮬레이션을 통해 확인하였다.