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.

中文翻译：

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无线网络中基于多武装匪盗的频谱调度算法：一项调查

将无线频谱的频带作为资源分配给用户是无线网络中的常见问题。通常，假定频段以稳定的方式可用。但是，在可能在未知环境中部署无线网络的最新场景中，考虑了频谱竞争，因此无法确定某个频段是否完全可用或质量如何。为了充分利用不确定性的资源，已将具有代表性的在线学习技术多臂匪（MAB）方法用于设计频谱调度算法。本文对此类建议进行了调查。我们描述了以下三个方面：如何在MAB框架内对频谱调度问题进行建模，设计主要算法遵循的主要线程是什么，以及如何评估算法性能和复杂度。我们还为相关领域的未来研究提供了一些有希望的方向。