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...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy:	Sung-Jeen Jang, Chul-Hee Han, Kwang-Eog Lee, Sang-Jo Yoo
Format:	Artykuł
Język:	English
Wydane:	SpringerOpen 2019-05-01
Seria:	EURASIP Journal on Wireless Communications and Networking
Hasła przedmiotowe:	Reinforcement learning Cognitive radio Ad-hoc network Q-learning Fairness
Dostęp online:	http://link.springer.com/article/10.1186/s13638-019-1433-1

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