RIS-Aided Ground-Aerial NOMA Communications: A Distributionally Robust DRL Approach-Reference-Cited by-同舟云学术

RIS-Aided Ground-Aerial NOMA Communications: A Distributionally Robust DRL Approach

Author:

Zhao Jingjing¹^ORCID,Yu Lanchenhui²^ORCID,Cai Kaiquan²^ORCID,Zhu Yanbo³^ORCID,Han Zhu⁴^ORCID

Affiliation:

1. Research Institute for Frontier Science, Beihang University, Beijing, China

2. National Key Laboratory of CNS/ATM, Beijing, China

3. School of Electronics and Information Engineering, Beihang University, Beijing, China

4. Electrical and Computer Engineering Department, University of Houston, Houston, TX, USA

Funder

Funds of the National Natural Science Foundation of China

U.S. National Science Foundation

Toyota Motor Corporation

Amazon Catalyst

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

Reference45 articles.

1. Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor;haarnoja;Proc Int Conf Mach Learn (ICML),2018

2. Benchmarking deep reinforcement learning for continuous control;duan;Proc Int Conf Mach Learn (ICML),2016

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