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학술대회 DNN-based Phase Noise Compensation for Sub-THz Communications
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저자
박형숙, 최은영, 송영석, 노송, 서경식
발행일
202010
출처
International Conference on Information and Communication Technology Convergence (ICTC) 2020, pp.866-868
DOI
https://dx.doi.org/10.1109/ICTC49870.2020.9289411
협약과제
20HH1300, [전문연구실] 초고주파 이동통신 무선백홀 전문연구실, 현석봉
초록
In this paper, a new method is presented for phase noise (PN) compensation in sub-TeraHertz (THz) orthogonal frequency division multiplexing (OFDM) systems. To suppress the higher PN encountered at the sub-THz spectrum bands, a deep neural network (DNN)-based PN compensation framework is proposed. Exploiting the signal under PN impairment and the channel estimate at the receiver, the proposed DNN framework makes hard decisions with respect to each data subcarrier. Numerical results show the effectiveness of the proposed framework.
키워드
deep neural network, OFDM, phase noise, Sub-TeraHertz communication
KSP 제안 키워드
Deep neural network(DNN), Numerical results, Orthogonal frequency division Multiplexing(OFDM), Sub-THz, THz communications, Terahertz Communication, new method, phase noise compensation, sub-terahertz