Reinforcement learning-based dynamic band and channel selection in cognitive radio ad-hoc networks

Reinforcement learning-based dynamic band and channel selection in cognitive radio ad-hoc networks

Abstract In cognitive radio (CR) ad-hoc network, the characteristics of the frequency resources that vary with the time and geographical location need to be considered in order to efficiently use them. Environmental statistics, such as an available transmission opportunity and data rate for each cha...

書誌詳細
主要な著者:	Sung-Jeen Jang, Chul-Hee Han, Kwang-Eog Lee, Sang-Jo Yoo
フォーマット:	論文
言語:	English
出版事項:	SpringerOpen 2019-05-01
シリーズ:	EURASIP Journal on Wireless Communications and Networking
主題:	Reinforcement learning Cognitive radio Ad-hoc network Q-learning Fairness
オンライン･アクセス:	http://link.springer.com/article/10.1186/s13638-019-1433-1

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