ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술지 A Supplementary Explanation for Experimental Environment of Implementation Methodologies of Deep Learning-based Signal Detection for Conventional MIMO Transmitters
Cited 1 time in scopus Download 10 time Share share facebook twitter linkedin kakaostory
저자
백명선, 곽상운, 정준영, 김흥묵, 최동준
발행일
202103
출처
IEEE Transactions on Broadcasting, v.67 no.1, pp.356-357
ISSN
0018-9316
출판사
IEEE
DOI
https://dx.doi.org/10.1109/TBC.2020.3028345
협약과제
19ZR1500, 동일 채널에서의 기계 학습 기반 다중 RF 신호 송수신 기술 개발, 최동준
초록
To solve practical challenges for implementing deep learning-based algorithm in MIMO signal detector such as handling complex number or designing proper neural network for a specific communication system, (Baek et al., 2019) has proposed candidate implementation methodologies with simple verification experiments. According to (Baek et al., 2019), it was shown that the proposed algorithms can achieve the optimal ML performance. However, due to the lack of explanation on the experimental environment, it is difficult for readers to reproduce the presented experiments and obtain the same results. This document precisely explains on the experimental environments of (Baek et al., 2019) including the exact channel profiles.
키워드
Deep learning, MIMO channel profiles, MIMO deep, MIMO detection, MIMO system
KSP 제안 키워드
Communication system, Complex Number, Learning-based, MIMO channel, MIMO detection, MIMO system, MIMO transmitters, Neural networks, Signal detector, Verification experiments, deep learning(DL)