Dynamic spectrum access is essential for radiocommunication and its limited spectrum resources. The key element of dynamic spectrum access systems is effective spectrum occupancy detection. In many cases, machine learning algorithms improve detection effectiveness. Because of the recent trend of using federated learning, a federated learning algorithm is presented in the context of distributed spectrum occupancy detection. The results of the work presented in the paper are based on actual signal samples collected in the laboratory. The proposed algorithm is effective, especially in the context of a set of sensors with faulty sensors.

翻译：动态频谱接入对于无线通信及其有限的频谱资源至关重要。动态频谱接入系统的核心要素是有效的频谱占用检测。在许多情况下，机器学习算法能够提升检测效能。鉴于当前联邦学习的使用趋势，本文提出了一种面向分布式频谱占用检测的联邦学习算法。研究成果基于实验室采集的实际信号样本。实验表明，所提出的算法在存在故障传感器的传感器组场景下尤为有效。