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...
Main Authors: | Sung-Jeen Jang, Chul-Hee Han, Kwang-Eog Lee, Sang-Jo Yoo |
---|---|
格式: | Article |
語言: | English |
出版: |
SpringerOpen
2019-05-01
|
叢編: | EURASIP Journal on Wireless Communications and Networking |
主題: | |
在線閱讀: | http://link.springer.com/article/10.1186/s13638-019-1433-1 |
相似書籍
-
Q-Learning Based Multi-Objective Clustering Algorithm for Cognitive Radio Ad Hoc Networks
由: Md Arman Hossen, et al.
出版: (2019-01-01) -
Mobilized ad-hoc networks: A reinforcement learning approach
由: Chang, Yu-Han, et al.
出版: (2005) -
Mobilized ad-hoc networks: A reinforcement learning approach
由: Chang, Yu-Han, et al.
出版: (2004) -
Reinforcement Learning Environment for Advanced Vehicular Ad Hoc Networks Communication Systems
由: Lincoln Herbert Teixeira, et al.
出版: (2022-06-01) -
Unified spectrum handoff in cognitive radio mobile ad hoc networks /
由: Samad Nejatian, 1981-, author 580992, et al.
出版: (2014)