Multi-Agent Deep Reinforcement Learning-Based Cooperative Spectrum Sensing With Upper Confidence Bound Exploration

Multi-Agent Deep Reinforcement Learning-Based Cooperative Spectrum Sensing With Upper Confidence Bound Exploration

In this paper, a multi-agent deep reinforcement learning method was adopted to realize cooperative spectrum sensing in cognitive radio networks. Each secondary user learns an efficient sensing strategy from the sensing results of some of the selected spectra to avoid interference to the primary user...

Full description

Bibliographic Details
Main Authors: Yu Zhang, Peixiang Cai, Changyong Pan, Subing Zhang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Cooperative spectrum sensing
deep reinforcement learning
cognitive radio
upper bound confidence
Online Access:https://ieeexplore.ieee.org/document/8811461/

Internet

https://ieeexplore.ieee.org/document/8811461/

Similar Items