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학술대회 Convolutional Autoencoder for Compressive Symbol Detection
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저자
박재혁, 김유경
발행일
201810
출처
International Conference on Information and Communication Technology Convergence (ICTC) 2018, pp.986-988
DOI
https://dx.doi.org/10.1109/ICTC.2018.8539605
협약과제
18HF1100, 압축센싱, 무전원 및 초고속체 전송 기반 무선통신 효율극대화 연구, 이우용
초록
This paper deals with a problem of digital communication which samples a signal compressively below its symbol rate and restores the original message symbols. We propose a method to optimize the sensing and restoration modules by designing them as the encoder and decoder of a convolutional autoencoder. The network learns end-to-end through simulation data. Our architecture has an efficient mechanism to solve this compressive symbol detection problem and it shows strong performance and fast speed empirically.
KSP 제안 키워드
Convolutional auto-encoder, Digital Communication, Encoder and Decoder, End to End(E2E), Fast speed, Simulation data, symbol detection, symbol rate