Details

Autor(en) / Beteiligte

• Aref, Mohamed A
• Jayaweera, Sudharman K
• Yepez, Esteban

Titel

Survey on cognitive anti-jamming communications

Ist Teil von

• IET communications, 2020-11, Vol.14 (18), p.3110-3127

Ort / Verlag

The Institution of Engineering and Technology

Erscheinungsjahr

2020

Link zum Volltext

Quelle

EZB-FREE-00999 freely available EZB journals

Beschreibungen/Notizen

• 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.