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Study on Underwater Acoustic Network Fairness Transmission Method Based on Deep Reinforcement Learning

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成果类型:
会议论文
作者:
Zhicheng Bi;Jinfeng Xiao;Chaofeng Wang
作者机构:
[Zhicheng Bi; Jinfeng Xiao; Chaofeng Wang] School of Electrical Engineering, University of South China, Hengyang, Hunan, China [email protected]
语种:
英文
年:
2025
页码:
309-313
会议名称:
AISNS '24: Proceedings of the 2024 2nd International Conference on Artificial Intelligence, Systems and Network Security
出版地:
New York, NY, United States
出版者:
Association for Computing Machinery
ISBN:
9798400711237
机构署名:
本校为第一机构
院系归属:
电气工程学院
摘要:
Underwater acoustic communication networks can satisfy the need for long-distance reliable communication for underwater node, serving as a key technology for the informatization and intelligentization of such communication. However, due to the use of sound waves as a carrier for information, underwater acoustic networks face complex challenges such as long propagation delays, severe channel attenuation, multipath effects, and environmental noise. To enhance the communication efficiency and reduce network congestion of underwater acoustic networks, this study proposes a MAC protocol based on de...

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