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Risk-sensitive spatio-temporal graph reinforcement learning for predictive and propulsion-aware routing in 6G-enabled FANETs

Flying ad hoc networks (FANETs) in 6G environments require routing schemes that can cope with rapid topology changes, limited UAV energy resources, and unstable air-to-air links. This paper proposes a...

Author: Nguyen Thu Thi

Keyword: 6G-enabled FANETs Spatio temporal graph learning Risk sensitive deep reinforcement learning Propulsion aware routing Route survival probability

Vinh University journal of science

Tạp chí khoa học Trường Đại học Vinh

ISSN: 1859 - 2228

Governing body: Vinh University

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License: 163/GP-BTTTT issued by the Minister of Information and Communications on May 10, 2023

Open Access License: Creative Commons CC BY NC 4.0

 

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