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...

Полное описание

Библиографические подробности
Главные авторы:	Sung-Jeen Jang, Chul-Hee Han, Kwang-Eog Lee, Sang-Jo Yoo
Формат:	Статья
Язык:	English
Опубликовано:	SpringerOpen 2019-05-01
Серии:	EURASIP Journal on Wireless Communications and Networking
Предметы:	Reinforcement learning Cognitive radio Ad-hoc network Q-learning Fairness
Online-ссылка:	http://link.springer.com/article/10.1186/s13638-019-1433-1

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