Dynamic Cooperative Spectrum Sensing Based on Deep Multi-User Reinforcement Learning
Dynamic spectrum access (DSA) has been considered as a promising technology to address spectrum scarcity and improve spectrum utilization. Normally, the channels are related to each other. Meanwhile, collisions will be inevitably caused by communicating between multiple PUs or multiple SUs in a real...
Main Authors: | Shuai Liu, Jing He, Jiayun Wu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-02-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/11/4/1884 |
Similar Items
-
Multi-Agent Deep Reinforcement Learning-Based Cooperative Spectrum Sensing With Upper Confidence Bound Exploration
by: Yu Zhang, et al.
Published: (2019-01-01) -
Reputation-Based Spectrum Sensing Strategy Selection in Cognitive Radio Ad Hoc Networks
by: Zhiguo Sun, et al.
Published: (2018-12-01) -
Dynamic Multichannel Sensing in Cognitive Radio: Hierarchical Reinforcement Learning
by: Shuai Liu, et al.
Published: (2021-01-01) -
Malicious Cognitive User Identification Algorithm in Centralized Spectrum Sensing System
by: Jingbo Zhang, et al.
Published: (2017-11-01) -
Deep Reinforcement Learning Based Dynamic Spectrum Competition in Green Cognitive Virtualized Networks
by: Quang Vinh Do, et al.
Published: (2021-01-01)