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압축센싱기법을 이용한 가시광 무선링크 전송용량 증가기술 연구
정의석(Jung, Eui-Suk),이용태(Lee, Yong-Tae),한상국(Han, Sang-Kook) 한국산학기술학회 2014 한국산학기술학회논문지 Vol.15 No.10
본 논문에서, 가시광 발광 다이오드를 데이터 전송용 광원으로 사용하는 광무선 전송 시스템의 채널 용량을 증가시키 는 새로운 기법을 제안하였다. 압축센싱을 기반으로 하는 적응형 샘플링 기법과 L1최소화 기법을 이용하여 직교 주파수 분할 다중방식기반 직교 위상천이 변조 (OFDM-QPSK: orthogonal frequency division multiplexed-qudarature phase shift keying) 데이터를 압축무선 전송한후, 수신단에서 복원하였다. 제안된 기법을 실험적으로 검증하기 위해서 소규모 링크를 이용하여 전송실험한 결과, OFDM-QPSK 데이터 전송률이 30.72Mb/s에서 51.2Mb/s로 증가함을 확인하였다. 이때의 오류벡 터크기(EVM: error vector magnitude)값은 31%이었고, 에러정정 코드를 적용할 경우, 완벽하게 복원 가능함을 확인하였다. A new technique, which can increase the channel bandwidth in an optical wireless orthogonal frequency division multiplexing (OFDM) link based on a light emitting diode (LED), is proposed. The technique uses adaptive sampling to convert an OFDM signal to a sparse waveform. In compressive sensing (CS), a sparse signal that is sampled below the Nyquist/Shannon limit can be reconstructed successively with sufficient measurements. The data rate of the proposed CS-based visible light communication (VLC)-OFDM link increases from 30.72 Mb/s to 51.2 Mb/s showing an error vector magnitude (EVM) of 31 % at the quadrature phase shift keying (QPSK) symbol.
Downlink Pilot Reduction for Massive MIMO Systems via Compressed Sensing
Jun Won Choi,Byonghyo Shim,Seok-Ho Chang IEEE 2015 IEEE communications letters Vol.19 No.11
<P>This letter addresses a problem of downlink pilot allocation for massive multiple-input multiple-output (MIMO) systems. When a massive MIMO is employed in frequency division duplex (FDD) systems, significant amount of radio resources are dedicated to the transmission of downlink pilots. Such huge pilot overhead leads to a substantial loss in the maximum data throughput, which motivates us to reduce the number of pilots. In this letter, we propose a pilot reduction strategy based on compressed sensing techniques for orthogonal frequency division multiplexing systems. The pilots are randomly located in a low density manner over the time and frequency domain. To estimate the channels with such low density pilots, we propose a novel sparse channel estimation technique that exploits the common support of the consecutive channel impulse responses over the certain time duration. The evaluation shows that for a massive MIMO with 128 antennas, the proposed scheme achieves significant reduction of pilot overhead, while maintaining good channel estimation performance.</P>
Roll-to-Roll Gravure Printed Electrochemical Sensors for Wearable and Medical Devices
Bariya, Mallika,Shahpar, Ziba,Park, Hyejin,Sun, Junfeng,Jung, Younsu,Gao, Wei,Nyein, Hnin Yin Yin,Liaw, Tiffany Sun,Tai, Li-Chia,Ngo, Quynh P.,Chao, Minghan,Zhao, Yingbo,Hettick, Mark,Cho, Gyoujin,Jav American Chemical Society 2018 ACS NANO Vol.12 No.7
<P>As recent developments in noninvasive biosensors spearhead the thrust toward personalized health and fitness monitoring, there is a need for high throughput, cost-effective fabrication of flexible sensing components. Toward this goal, we present roll-to-roll (R2R) gravure printed electrodes that are robust under a range of electrochemical sensing applications. We use inks and electrode morphologies designed for electrochemical and mechanical stability, achieving devices with uniform redox kinetics printed on 150 m flexible substrate rolls. We show that these electrodes can be functionalized into consistently high performing sensors for detecting ions, metabolites, heavy metals, and other small molecules in noninvasively accessed biofluids, including sensors for real-time, <I>in situ</I> perspiration monitoring during exercise. This development of robust and versatile R2R gravure printed electrodes represents a key translational step in enabling large-scale, low-cost fabrication of disposable wearable sensors for personalized health monitoring applications.</P> [FIG OMISSION]</BR>
Collaborative Framework of Algorithms for Sparse Channel Estimation in OFDM Systems
Anthony Ngozichukwuka Uwaechia,Nor Muzlifah Mahyuddin 한국통신학회 2018 Journal of communications and networks Vol.20 No.1
For proper matrix ensembles, it has been known that thegreedy pursuit (GP) algorithms are computationally efficient andfast to reconstruct sparse signals from far fewer linear measurements. In considering several parameters such as sparsity level,sparse signal ambient dimension and the number of linear measurements,the GP algorithms have been shown to perform differentlyin estimating sparse signals. According to data fusion principle,fusing completely the estimated support set of different reconstructionalgorithms can improve signal recovery performance. Itcan, however, lead to the increased probability of estimating incorrectsupport indices, and thus degrades the signal reconstructionaccuracy. In this paper, a new fusion framework, namely collaborativeframework of algorithms (CoFA), is proposed to pursueaccurate reconstruction of the sparse signals from far fewerlinear measurements. The two main ingredients of the proposedscheme that control the estimation of incorrect support indices arepre-selection support of orthogonal matching pursuit (OMP) algorithmand Thresholding -to eliminate unpromising indices fromthe identied support set of any participating algorithm. Using therestricted isometry property, the theoretical analysis of the CoFAscheme and the sufficient conditions (guarantees) for realizing animproved reconstruction performance are presented. Simulationresults demonstrate that the proposed scheme is effective and offera better channel estimation performance in terms of meansquared-error (MSE) and bit-error-rate (BER) when compared toother reconstruction algorithms, without the significant increase incomputational complexity.