• 한국통신학회논문지
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• 제35권5A호
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• pp.490-495
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• 2010

본 논문에서는 DFT를 활용한 순차적 스펙트럼 센싱 알고리즘을 제안한다. 기존의 FFT를 이용한 센싱 알고리즘의 경우 FFT의 특성상 한번에 모든 주파수 성분을 구하여 임계값과 비교하는 구조로 불필요한 계산량을 포함하고 있다. 제안하는 센싱 알고리즘에서는 DFT를 활용하여 우선순위에 따라서 주파수 성분을 순차적으로 구하고 이를 임계값과 비교하여 신호의 존재 여부를 판단한다. 제안하는 센싱 알고리즘은 기존의 FFT를 이용한 센싱 알고리즘과 유사한 검출 성능을 제공하면서 신호의 조기 검출 여부에 따라 스펙트럼 센싱에 필요한 계산량을 현저하게 줄일 수 있다.

• 디지털산업정보학회논문지
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• 제7권3호
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• pp.75-83
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• 2011

Cognitive radio (CR) technology is to maximize the spectrum utilization by allocating the unused spectrums to the unlicensed users. This technology enables the sharing of channels among secondary (unlicensed) and primary (licensed) users on a non-interference basis after sensing the vacant channel and as a result, it is possible to harness wireless frequency more efficiently. To enhance the accuracy of sensing, RDSS was suggested. It is a fusion mechanism based on the reputation of sensing nodes and WSPRT (weighted sequential probability ratio test). However, in RDSS, the execution number of WSPRT could increase according to the order of inputted sensing values, and the fast defense against the forged values is difficult. In this paper, we propose a transaction signing-based authentication scheme for secure distributed spectrum sensing to response the forged values. The validity of proposed scheme is provided by BAN logic.

• Journal of Information Processing Systems
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• 제15권6호
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• pp.1335-1349
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• 2019

Crowdsensing technologies can improve the efficiency of smart parking system in comparison with present sensor based smart parking system because of low install price and no restriction caused by sensor installation. A lot of sensing data is necessary to predict parking lot saturation in real-time. However in real world, it is hard to reach the required number of sensing data. In this paper, we model a saturation predication combining a time-based prediction model and a sensing data-based prediction model. The time-based model predicts saturation in aspects of parking lot location and time. The sensing data-based model predicts the degree of saturation of the parking lot with high accuracy based on the degree of saturation predicted from the first model, the saturation information in the sensing data, and the number of parking spaces in the sensing data. We perform prediction model learning with real sensing data gathered from a specific parking lot. We also evaluate the performance of the predictive model and show its efficiency and feasibility.

• Journal of information and communication convergence engineering
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• 제9권1호
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• pp.27-31
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• 2011

This paper describes the optimization of spectrum sensing in terms of the throughput of a cognitive radio (CR) system. Dealing with the optimization problem of spectrum sensing, this paper evaluates the throughput of a CR system by considering such situations as the penalty time of a channel search and incumbent user (IU) detection delay caused by a missed detection of an incumbent signal. Also, this paper suggests a serial channel search scheme as the search method for a vacant channel, and derives its mean channel search time by considering the penalty time due to the false alarm of a vacant channel search. The numerical results suggest the optimum sensing time of the channel search process using the derived mean channel search time of a serial channel search in the case of a sensing hardware structure with single radio frequency (RF) path. It also demonstrates that the average throughput is improved by two separate RF paths in spite of the hardware complexity of an RF receiver.

• Journal of information and communication convergence engineering
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• 제11권4호
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• pp.223-228
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• 2013

Cognitive radio has been recently considered a promising technology to improve spectrum utilization by enabling secondary access to licensed bands that are not used by primary users temporarily or spatially. A prerequisite to this secondary access is the lack of interference to the primary system. This requirement makes spectrum sensing a key process for cognitive radio. In this study, we consider amplify and forward (AF)-based cooperative spectrum sensing for cognitive radio networks where multiple relay nodes are utilized to amplify and forward the primary user signal for better spectrum sensing, and maximum ratio combining is used for fusion detection by a cognitive coordinator. Further, the detection probability and the bit error rate of AF-based cooperative spectrum sensing are analyzed in fading multiple cognitive relay channels. The simulation results show that the AF-based cooperative spectrum sensing scheme outperforms the conventional scheme.

• 한국통신학회논문지
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• 제35권4C호
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• pp.364-370
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• 2010

본 논문에서는 무선인지 시스템에서 궤환 오류를 고려한 협력 스펙트럼 센싱 기법에 대해서 제안한다. 협력 센싱에서는 각 부사용자의 자체 센싱 결과를 결합하여 최종 판정을 내리게 되는데, 부사용자가 정확한 자체 센싱결과를 내리더라도 궤환 채널의 상태가 좋지 않은 경우 이를 협력 센싱을하는데 직접적으로 사용할 수 없게 된다. 본 논문에서는 궤환 채널 상태가 좋은 사용자만 선택하여 협력 센싱에 참여하도록 함으로써 목표 오검출 확률을 만족하면서 정검출 확률을 최대화 시키는 협력 센싱 기법에 대해 제안한다.

• Wind and Structures
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• 제15권5호
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• pp.369-383
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• 2012

Researchers have recently begun using high spatial resolution remote-sensing data, which are automatically captured and georeferenced, to assess damage following natural and man-made disasters, in addition to, or instead of employing the older methods of walking house-to-house for surveys, or photographing individual buildings from an airplane. This research establishes quantitative relationships between the damage states observed at ground-level, and those observed from space using high spatial resolution remote-sensing data, for windstorms, for individual site-built one- or two-family residences (FR12). "Degrees of Damage" (DOD) from the Enhanced Fujita (EF) Scale were determined for ground-based damage states; damage states were also assigned for remote-sensing imagery, using a modified version of Womble's Remote-Sensing (RS) Damage Scale. The preliminary developed model can be used to predict the ground-level damage state using remote-sensing imagery, which could significantly lessen the time and expense required to assess the damage following a windstorm.

• 대한전자공학회논문지SP
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• 제46권5호
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• pp.15-24
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• 2009

Compressed sensing은 소수의 선형 관측으로부터 sparse 신호를 복원하는 문제를 언급하고 있다. 최근 벡터 경우에서의 성공적인 연구 결과가 행렬의 경우로 확장되었다. Low-rank 행렬의 compressed sensing은 ill-posed inverse problem을 low-rank 정보를 이용하여 해결한다. 본 문제는 rank 최소화 혹은 low-rank 근사의 형태로 나타내질 수 있다. 본 논문에서는 최근 제안된 여러 가지 효율적인 알고리즘에 대한 survey를 제공한다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1365-1367
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• 2003

A new method, called dynamic space projection method that is suitable to remote sensing image, is adopted to encrypt GCP (ground control point) datum in this paper. The essence of this method is to encrypt enough GCP by using a few known GCP in order to realize the precise correction of remote sensing image. By making use of the method to the GCP datum encrypting and precise geometric correction of TM image and SPOT image, the precision of encrypted GCP is less than one pixel, the precision of precisely corrected image is less than two pixels.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1359-1361
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• 2003

A set of microwave remote sensing data collected with the newly developed UMass Imaging Wind and Rain Airborne Profiler (IWRAP) during the 2002 Atlantic Hurricane Season was analyzed to further our understanding of the effect of precipitation on scatterometer wind vector retrieval. Coincident surface wind speed and precipitation measurements were provided by the UMass Simultaneous Frequency Microwave Radiometer (SFMR). The differences between the wind estimations from IWRAP and SFMR under precipitation conditions of 0-100mm/hr and wind speed of 0-60m/s was calculated, from which the effect of precipitation on the wind vector retrieval using scatterometry is analyzed qualitatively.