NDLI: Survey on cognitive anti-jamming communications

Content Provider	IET Digital Library
Author	Aref, Mohamed A. Jayaweera, Sudharman K. Yepez, Esteban
Abstract	In this study, the authors review various jamming and anti-jamming strategies in the context of cognitive radios (CRs). The study explores different jamming models and classifies them according to their functionality. Furthermore, a study of jamming detection techniques is provided to enable a CR to identify different jamming signals. Finally, anti-jamming communications are discussed in detail to encounter different types of jamming attacks. The focus of the study is on advanced anti-jamming approaches that are based on learning strategies including, for example, game theoretic learning, reinforcement learning and deep learning. They show differences and similarities between these approaches and the conditions under which each of the algorithms can be useful.
Starting Page	3110
Ending Page	3127
Page Count	18
ISSN	17518628
Volume Number	14
e-ISSN	17518636
Issue Number	Issue 18, Nov (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/14/18
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2020.0024
Journal	IET Communications
Publisher Date	2020-05-21
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Advanced Anti-jamming Approach Anti-jamming Strategy Cognitive Anti-jamming Communication Cognitive Radio Cognitive Radios Detection Technique Different Jamming Model Different Jamming Signal Electromagnetic Compatibility Game Theoretic Learning Game Theory Interference Jamming Jamming Attack Knowledge Engineering Technique Learning in AI Learning Strategy Radio Link And Equipment
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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