Sum Throughput Maximization Scheme for NOMA-Enabled D2D Groups Using Deep Reinforcement Learning in 5G and Beyond Networks-Reference-Cited by-同舟云学术

Sum Throughput Maximization Scheme for NOMA-Enabled D2D Groups Using Deep Reinforcement Learning in 5G and Beyond Networks

Author:

Khan Mohammad Aftab Alam¹^ORCID,Kaidi Hazilah Mad²^ORCID,Ahmad Norulhusna²^ORCID,Rehman Masood Ur³

Affiliation:

1. Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

2. Department of Engineering and Technology, Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

3. Electronics and Telecommunication Engineering, James Watt School of Engineering, University of Glasgow, Glasgow, U.K.

Funder

Ministry of Higher Education under Fundamental Research Grant Scheme

National Institute of Information and Communications Technology (NICT) under ASEAN IVO Project 2022: Agricultural IoT Based on Edge Computing

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

Reference42 articles.

4. Policy gradient methods for reinforcement learning with function approximation;sutton;Proc Adv Neural Inf Process Syst,2000

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