Deep Learning Aided Routing for Space-Air-Ground Integrated Networks Relying on Real Satellite, Flight, and Shipping Data-Reference-Cited by-同舟云学术

Deep Learning Aided Routing for Space-Air-Ground Integrated Networks Relying on Real Satellite, Flight, and Shipping Data

Author:

Liu Dong¹,Zhang Jiankang²,Cui Jingjing³,Ng Soon-Xin³,Maunder Robert G.³,Hanzo Lajos³

Affiliation:

1. Beihang University,China

2. Bournemouth University,England

3. University of Southampton,England

Funder

Engineering and Physical Sciences Research Council

European Research Council's

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications

Link

Reference15 articles.

2. Multiobjective Optimization for Integrated Ground-Air-Space Networks;cui;IEEE Vehic Tech Mag,2021

Cited by 20 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

3. Q-learning for distributed routing in LEO satellite constellations;2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN);2024-05-05

4. Multi-Agent Deep Reinforcement Learning for Distributed Satellite Routing;2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN);2024-05-05

5. SAGIN-CAIN: A 3D Routing Protocol for Post-Disaster SAGIN 6G Network;2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT);2024-04-29