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.

中文翻译：

---

认知抗干扰交流研究

在这项研究中，作者回顾了认知无线电（CR）背景下的各种干扰和抗干扰策略。该研究探索了不同的干扰模型，并根据其功能对其进行分类。此外，提供了对干扰检测技术的研究，以使CR能够识别不同的干扰信号。最后，详细讨论了抗干扰通信以遇到不同类型的干扰攻击。该研究的重点是基于学习策略的高级抗干扰方法，包括游戏理论学习，强化学习和深度学习。它们显示了这些方法与每种算法可使用的条件之间的异同。