• 한국소음진동공학회논문집
• /
• 제25권11호
• /
• pp.787-797
• /
• 2015

In this paper, a cochlea-inspired artificial filter bank(CAFB) was developed in order to efficiently acquire dynamic response of structure, and it was also evaluated via dynamic response experiments. To sort out signals containing significant modal information from all the dynamic responses of structure, it was made to adopt a band-pass filter optimizing algorithm(BOA) and a peak-picking algorithm (PPA). Optimally designed on the basis of El-centro and Kobe earthquake signals, it was then embedded into the wireless multi-measurement system(WiMMS). In order to evaluate the performance of the developed CAFB, a vibration test was conducted using the El-centro and Kobe earthquake signals, and structural responses of a two-span bridge were obtained and analyzed simultaneously by both a wired measurement system and a CAFB-based WiMMS. The test results showed that the compressed dynamic responses acquired by the CAFB-based WiMMS matched with those of the wired system, and they included significant modal information of the two-span bridge. Therefore this study showed that the developed CAFB could be used as a new, economic, and efficient measurement device for wireless sensor networks(WSNs) based real time structural health monitoring because it could reconstruct the whole dynamic response using the compressed dynamic response with significant modal information.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권10호
• /
• pp.4678-4702
• /
• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.

• 한국산업정보학회논문지
• /
• 제23권6호
• /
• pp.47-58
• /
• 2018

최근에 원거리 비디오 센싱과 같은 응용은 많은 무선 네트워크에 중요한 응용으로 크게 관심을 받고 있다. 분산 압축 비디오 센싱기술은 높은 부호화 복잡도를 간단히 하고, 동시에 비디오 데이터를 캡처함과 동시에 압축함으로써 이 분야에 적용 가능한 기술로 고려되고 있다. 특히, 움직임 보상 블록 압축센싱 기술인 MC-BCS-SPL은 분산 압축 비디오 센싱 방법 중에 효과적인 기술로서 고려되고 있으나, 복원된 위너-지브 프레임에서 우수하지 못한 성능을 제공한다. 본 논문에서는 기존의 MC-BCS-SPL 알고리즘을 살펴보고, 이웃하는 키프레임 사이에 신뢰성에 기초하여 효과적으로 움직임 보상 프레임을 얻는 방법을 도입함으로써 우수한 화질을 제공하는 방법을 제안한다. 다양한 실험 결과를 통하여 제안한 알고리즘은 기존의 알고리즘에 비해 우수한 화질을 제공할 수 있음을 확인한다.

• 대한전자공학회논문지TC
• /
• 제48권11호
• /
• pp.67-72
• /
• 2011

본 논문은 에너지 검출기를 사용하여 1차 사용자를 감지하는 경우, 압축 감지 기술을 채용하여 나이퀴스트율 보다 낮은 표본화율을 사용하여 기존의 에너지 검출기만으로 기존보다 넓은 주파수 대역을 감지하는 경우를 가정한다. 스즈키 채널 하에서 시뮬레이션을 통해 넓은 주파수 대역을 센싱하는 과정에서 나이퀴스트 표본화율보다 낮은 표본화률에 따른 오보확률과 감지확률을 통해 센싱 성능을 고찰한다.

• Journal of Communications and Networks
• /
• 제18권1호
• /
• pp.95-104
• /
• 2016

Massive multiple-input multiple-output (MIMO) is a promising approach for cellular communication due to its energy efficiency and high achievable data rate. These advantages, however, can be realized only when channel state information (CSI) is available at the transmitter. Since there are many antennas, CSI is too large to feed back without compression. To compress CSI, prior work has applied compressive sensing (CS) techniques and the fact that CSI can be sparsified. The adopted sparsifying bases fail, however, to reflect the spatial correlation and channel conditions or to be feasible in practice. In this paper, we propose a new sparsifying basis that reflects the long-term characteristics of the channel, and needs no change as long as the spatial correlation model does not change. We propose a new reconstruction algorithm for CS, and also suggest dimensionality reduction as a compression method. To feed back compressed CSI in practice, we propose a new codebook for the compressed channel quantization assuming no other-cell interference. Numerical results confirm that the proposed channel feedback mechanisms show better performance in point-to-point (single-user) and point-to-multi-point (multi-user) scenarios.

• 한국음향학회지
• /
• 제36권6호
• /
• pp.394-400
• /
• 2017

본 논문은 기존의 시간영역에서 다루던 공분산 행렬 fitting 기반 도래각 추정 알고리즘인 SpSF(Sparse Spectrum Fitting)를 주파수 영역으로 확장함으로써 기존의 시간영역의 SpSF 알고리즘이 주파수 영역에서도 구현 가능함을 보인다. 기존의 주파수 영역에서 구현되는 도래각 추정 알고리즘과의 성능 분석 및 비교를 통해 압축센싱 기반 공분산 fitting 알고리즘인 SpSF의 우수함을 보여준다.

• 한국통신학회논문지
• /
• 제40권12호
• /
• pp.2476-2484
• /
• 2015

배의 방사 소음을 이용하여 배를 탐지하는 데는 협대역 톤을 추정하는 방법과 광대역 신호에 내포된 주기성 신호를 추정하는 방법이 있다. 그 중에서 광대역 신호에 내포된 주기성 신호를 추정하는 방법을 데몬 신호 처리법이라고 한다. 본 논문에서는 데몬 처리를 위해서 압출 센싱 기법을 자기 상관기 필터 뱅크에 적용한 기법을 제안한다. 그리고 합성된 신호와 실제 신호를 바탕으로 기존 방법들과 비교하여 기본 주파수 신호를 우수하게 추정할 뿐만 아니라 기존 방법에 비해서 짧은 신호 길이를 사용해도 우수한 성분 추정 성능을 할 수 있음을 보인다.

• Investigative Magnetic Resonance Imaging
• /
• 제19권1호
• /
• pp.19-30
• /
• 2015

Purpose: A new compressed sensing technique by iterative truncation of small transformed coefficients (ITSC) is proposed for fast cardiac CINE MRI. Materials and Methods: The proposed reconstruction is composed of two processes: truncation of the small transformed coefficients in the r-f domain, and restoration of the measured data in the k-t domain. The two processes are sequentially applied iteratively until the reconstructed images converge, with the assumption that the cardiac CINE images are inherently sparse in the r-f domain. A novel sampling strategy to reduce the normalized mean square error of the reconstructed images is proposed. Results: The technique shows the least normalized mean square error among the four methods under comparison (zero filling, view sharing, k-t FOCUSS, and ITSC). Application of ITSC for multi-slice cardiac CINE imaging was tested with the number of slices of 2 to 8 in a single breath-hold, to demonstrate the clinical usefulness of the technique. Conclusion: Reconstructed images with the compression factors of 3-4 appear very close to the images without compression. Furthermore the proposed algorithm is computationally efficient and is stable without using matrix inversion during the reconstruction.

• Journal of Communications and Networks
• /
• 제15권3호
• /
• pp.283-291
• /
• 2013

In this paper, we propose new multiuser detectors (MUDs) based on compressed sensing approaches for the large-scale multiple antenna systems equipped with dozens of low-power antennas. We consider the scenarios where the number of receiver antennas is smaller than the total number of users, but the number of active users is relatively small. This prior information motivates sparsity-embracing MUDs such as sparsity-embracing linear/nonlinear MUDs where the detection of active users and their symbol detection are employed. In addition, sparsity-embracing MUDs with maximum a posteriori probability criterion (MAP-MUDs) are presented. They jointly detect active users and their symbols by exploiting the probability of user activity, and it can be solved efficiently by introducing convex relaxing senses. Furthermore, it is shown that sparsity-embracing MUDs exploiting common users' activity across multiple symbols, i.e., frame-by-frame, can be considered to improve performance. Also, in multiple multiple-input and multiple-output networks with aggressive frequency reuse, we propose the interference cancellation strategy for the proposed sparsity-embracing MUDs. That first cancels out the interference induced by adjacent networks and then recovers the desired users' information by exploiting the low user activity. In simulation studies for binary phase shift keying modulation, numerical evidences establish the effectiveness of our proposed MUDs exploiting low user activity, as compared with the conventional MUD.

• 한국위성정보통신학회논문지
• /
• 제9권4호
• /
• pp.104-110
• /
• 2014

본 논문에서는 무인항공기인 방송용 멀티콥터를 이용한 Full-HD급 이상 화질의 이미지를 효율적으로 전송하기 위해 이미지 압축 센싱 기법을 적용하고, Sparse 신호의 효율적 복원을 위해 Turbo 알고리즘과 Markov chain Monte Carlo (MCMC) 알고리즘의 복원 성능을 모의실험을 통해 비교 분석하였다. 제안된 복원 기법은 압축 센싱에 기반하여 데이터 용량을 줄이고 빠르고 오류 없는 원신호 복원에 중점을 두었다. 다수의 이미지 파일로 모의실험을 진행한 결과 Loopy belief propagation(BP) 기반의 Turbo 복원 알고리즘이 Gibbs sampling기반 알고리즘을 수행하는 MCMC 알고리즘 보다 평균 복원 연산 시간, NMSE 값에서 우수하여 보다 효율적인 복원 방법으로 생각된다.