< BK21 플러스 BEST 정보기술 사업단 세미나 개최 안내>
개최일시 : 2017년 12월 19일 화요일 14:00 ~ 15:00
개최장소 : 제1공학관 A442호
세미나 제목 : Inference from Randomized Transmissions by Many Backscatter Sensors
발표 초록 :
To attain the vision of Smart Cities, backscatter sensors have emerged to be a promising solution. However, backscatter sensors with limited signal-processing capabilities are unable to support conventional algorithms for multiple access and channel training. Thus, the key challenge in designing backscatter sensor networks is to enable readers to accurately detect sensing values given primitive transmission schemes and no knowledge of channel states and statistics. We tackle this challenge by proposing the novel framework of backscatter sensing (BackSense) featuring random encoding at backscatter sensors and statistical inference at readers. Specifically, assuming the widely used on/off keying for backscatter transmissions, the practical random-encoding scheme causes the on/off transmission of a sensor to be randomized and follow a distribution parameterized by the sensing values. Facilitated by the scheme, statistical inference algorithms are designed to enable a reader to infer sensing values from randomized transmissions by multiple backscatter sensors. The specific design procedure involves the construction of Bayesian networks, namely deriving conditional distributions for relating unknown parameters and variables to signals observed by the reader. Then based on the Bayesian networks and the well-known expectation-maximization principle, inference algorithms are derived to recover sensing values.
강연자 성함&직함 / 소속 : 고승우, Postdoctoral Researcher / The University of Hong Kong
초청자 : 전기전자공학과 교수 김성륜