Joint UAV 3D Trajectory Design and Resource Scheduling for Space-Air-Ground Integrated Power IoRT: A Deep Reinforcement Learning Approach-Reference-Cited by-同舟云学术

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Joint UAV 3D Trajectory Design and Resource Scheduling for Space-Air-Ground Integrated Power IoRT: A Deep Reinforcement Learning Approach

Published:2023 Issue: Volume: Page:1-15
ISSN:2327-4697
Container-title:IEEE Transactions on Network Science and Engineering
language:
Short-container-title:IEEE Trans. Netw. Sci. Eng.

Author:

Liu Jiayan¹^ORCID,Zhao Xiongwen¹^ORCID,Qin Peng¹^ORCID,Du Fei¹^ORCID,Chen Zhiyu²^ORCID,Zhou Hongxi²,Li Junqin³

Affiliation:

1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China

2. State Grid Information & Telecommunication Branch, Beijing, China

3. State Grid Beijing Electric Power Company, Beijing, China

Funder

Science and Technology Project of State Grid Corporation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/6488902/6930788/10373024.pdf?arnumber=10373024

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. Joint Optimization of Trajectory Control, Task Offloading, and Resource Allocation in Air-Ground Integrated Networks;IEEE Internet of Things Journal;2024-07-01

2. QoE Maximization for Video Streaming in Cache-Enable Satellite-UAV-Terrestrial Network;ICC 2024 - IEEE International Conference on Communications;2024-06-09

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