Learning From Noisy Labels for MIMO Detection With One-Bit ADCs
Author:
Affiliation:
1. Department of Electrical Engineering, POSTECH, Pohang, Republic of Korea
2. School of Electrical Engineering, Korea University, Seoul, Republic of Korea
3. Department of Electrical Engineering, Hanyang University, Seoul, Republic of Korea
Funder
National Research Foundation of Korea (NRF) Grant
Korea Government
BK21 FOUR Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/5962382/10063957/09993788.pdf?arnumber=9993788
Reference14 articles.
1. Training deep neural-networks based on unreliable labels
2. Maximum likelihood from incomplete data via the EM algorithm;dempster;J Roy Stat Soc,1977
3. MIMO Detection under Hardware Impairments via Learning from Noisy Labels
4. Machine Learning Detectors for MU-MIMO Systems With One-Bit ADCs
5. Supervised-Learning for Multi-Hop MU-MIMO Communications With One-Bit Transceivers
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