Real-Time Machine Learning Methods for Two-Way End-to-End Wireless Communication Systems-Reference-Cited by-同舟云学术

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Real-Time Machine Learning Methods for Two-Way End-to-End Wireless Communication Systems

Published:2022-11-15 Issue:22 Volume:9 Page:22983-22992
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Baek Seunghwan¹^ORCID,Moon Jihwan²^ORCID,Park Junhee³^ORCID,Song Changick⁴^ORCID,Lee Inkyu¹^ORCID

Affiliation:

1. School of Electrical Engineering, Korea University, Seoul, South Korea

2. Department of Mobile Convergence Engineering, Hanbat National University, Daejeon, South Korea

3. Network Division, Samsung Electronics, Suwon, South Korea

4. Department of Electronic Engineering, Korea National University of Transportation, Chungju, South Korea

Funder

National Research Foundation of Korea

Korea Government (MSIT) and the Ministry of Education

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/9939125/09809973.pdf?arnumber=9809973

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Self-Supervised Method for Accelerated Training of Neural Communication Receivers;2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN);2024-05-05

2. Training of Deep Joint Transmitter-Receiver Optimized Communication System without Auxiliary Tools;Electronics;2024-02-21

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