Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey

Assigning bands of the wireless spectrum as resources to users is a common problem in wireless networks. Typically, frequency bands were assumed to be available in a stable manner. Nevertheless, in recent scenarios where wireless networks may be deployed in unknown environments, spectrum competition...

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Bibliographic Details
Published in:IEEE wireless communications Vol. 27; no. 1; pp. 24 - 30
Main Authors: Li, Feng, Yu, Dongxiao, Yang, Huan, Yu, Jiguo, Karl, Holger, Cheng, Xiuzhen
Format: Journal Article
Language:English
Published: New York IEEE 01.02.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Frequencies
Interference
Machine learning
Multi-armed bandit problems
Probability distribution
Scheduling
Uncertainty
Unknown environments
Wireless networks
ISSN:1536-1284, 1558-0687
Online Access:Get full text
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Summary:Assigning bands of the wireless spectrum as resources to users is a common problem in wireless networks. Typically, frequency bands were assumed to be available in a stable manner. Nevertheless, in recent scenarios where wireless networks may be deployed in unknown environments, spectrum competition is considered, making it uncertain whether a frequency band is available at all or at what quality. To fully exploit such resources with uncertain availability, the multi-armed bandit (MAB) method, a representative online learning technique, has been applied to design spectrum scheduling algorithms. This article surveys such proposals. We describe the following three aspects: how to model spectrum scheduling problems within the MAB framework, what the main thread is following which prevalent algorithms are designed, and how to evaluate algorithm performance and complexity. We also give some promising directions for future research in related fields.
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ISSN:1536-1284
1558-0687
DOI:10.1109/MWC.001.1900280