Due to the openness of the transmission medium, it is necessary for radio systems to have anti-jamming abilities. Traditional anti-jamming methods such as sequence-based frequency hopping and direct sequence spread spectrum have shortcomings of low spectral efficiency and fixed communication patterns. With the development of software-defined radio, jamming devices are increasingly advanced and efficient. In this article, we propose a new paradigm for anti-jamming called DSAJ. With the help of cognitive radio and machine learning, the aim of DSAJ is to learn the dynamic and complex spectrum environment and obtain an optimal communication strategy. We first introduce the basic concept of anti-jamming communications and provide a brief summary of anti-jamming methods. Then, through a case study, mathematical modeling and applications of DSAJ are discussed for both single-user and multi-user systems. A real-life DSAJ testbed is described, and some potential research directions are discussed.

中文翻译：

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动态频谱抗干扰通信：挑战与机遇

由于传输介质的开放性，无线电系统必须具备抗干扰能力。传统的基于序列的跳频、直接序列扩频等抗干扰方法存在频谱效率低、通信模式固定等缺点。随着软件定义无线电的发展，干扰设备越来越先进和高效。在本文中，我们提出了一种新的抗干扰范式，称为 DSAJ。在认知无线电和机器学习的帮助下，DSAJ的目标是学习动态复杂的频谱环境并获得最优的通信策略。我们首先介绍了抗干扰通信的基本概念，并简要介绍了抗干扰方法。然后，通过案例研究，讨论了单用户和多用户系统的 DSAJ 数学建模和应用。描述了一个真实的 DSAJ 测试平台，并讨论了一些潜在的研究方向。