Machine Learning-Based Vision-Aided Beam Selection for mmWave Multiuser MISO System-Reference-Cited by-同舟云学术

Machine Learning-Based Vision-Aided Beam Selection for mmWave Multiuser MISO System

Published:2022-06 Issue:6 Volume:11 Page:1263-1267
ISSN:2162-2337
Container-title:IEEE Wireless Communications Letters
language:
Short-container-title:IEEE Wireless Commun. Lett.

Author:

Ahn Hyemin¹^ORCID,Orikumhi Igbafe¹^ORCID,Kang Jeongwan¹^ORCID,Park Hyunwoo¹^ORCID,Jwa Hyekyung²,Na Jeehyeon²,Kim Sunwoo¹^ORCID

Affiliation:

1. Department of Electronics and Computer Engineering, Hanyang University, Seoul, South Korea

2. Electronics and Telecommunications Research Institute, Daejeon, South Korea

Funder

Institute of Information and Communications Technology Planning Evaluation (IITP) grant funded by the Korea Government (MSIT, 5G Open Intelligence-Defined RAN

Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/5962382/9790070/09745525.pdf?arnumber=9745525

Reference17 articles.

1. You Only Look Once: Unified, Real-Time Object Detection

2. User Selection for Multiuser MIMO Downlink With Zero-Forcing Beamforming

3. Millimeter Wave and Sub-Terahertz Spatial Statistical Channel Model for an Indoor Office Building

4. Max-Min Fairness of K-User Cooperative Rate-Splitting in MISO Broadcast Channel With User Relaying

5. A Deep-Learning-Based Scheme for Detecting Driver Cell-Phone Use

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