Joint Optimization Design of RIS-Assisted Hybrid FSO SAGINs using Deep Reinforcement Learning-Reference-Cited by-同舟云学术

Joint Optimization Design of RIS-Assisted Hybrid FSO SAGINs using Deep Reinforcement Learning

Author:

Wu Min¹,Guo Kefeng¹^ORCID,Lin Zhi²,Li Xingwang³^ORCID,An Kang⁴^ORCID,Huang Yuzhen⁵^ORCID

Affiliation:

1. School of Space Information, Space Engineering University, Beijing, China

2. College of Electronic Engineering, National University of Defense Technology, Hefei, China

3. School of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo, China

4. Sixty-Third Research Institute, National University of Defense Technology, Nanjing, China

5. Academy of Military Sciences of PLA, Beijing, China

Funder

National Natural Science Foundation of China

Research Foundation of the Key Laboratory of Spaceborne Information Intelligent Interpretation

Electronic Information Equipment System Research National Defense Science and Technology Key Laboratory

Research Plan Project of NUDT

Young Elite Scientist Sponsorship Program of CAST

Macau Young Scholars Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

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