Refiner GAN Algorithmically Enabled Deep-RL for Guaranteed Traffic Packets in Real-Time URLLC B5G Communication Systems-Reference-Cited by-同舟云学术

Refiner GAN Algorithmically Enabled Deep-RL for Guaranteed Traffic Packets in Real-Time URLLC B5G Communication Systems

Published:2022 Issue: Volume:10 Page:50662-50676
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Salh Adeeb¹,Audah Lukman¹^ORCID,Kim Kwang Soon²^ORCID,Alsamhi Saeed Hamood³^ORCID,Alhartomi Mohammed A.⁴^ORCID,Abdullah Qazwan¹^ORCID,Almalki Faris A.⁵^ORCID,Algethami Haneen⁶^ORCID

Affiliation:

1. Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, Malaysia

2. School of Electrical & Electronics Engineering, Yonsei University, Seodaemun-gu, Seoul, South Korea

3. SRI, Technical University of the Shannon: Midlands Midwest, Athlone, Ireland

4. Department of Electrical Engineering, University of Tabuk, Tabuk, Saudi Arabia

5. Department of Computer Engineering, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia

6. Department of Computer Science, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09762938.pdf?arnumber=9762938

Reference39 articles.

1. Multi-Agent DRL for Task Offloading and Resource Allocation in Multi-UAV Enabled IoT Edge Network

2. Spectrum Sharing in Vehicular Networks Based on Multi-Agent Reinforcement Learning

3. An Introduction to Reinforcement Learning

4. Deep Reinforcement Learning Based Resource Allocation for V2V Communications

5. Comments on “Dual methods for nonconvex spectrum optimization of multicarrier systems”

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