We present a novel method for centralized collaborative spectrum sensing for IoT network leveraging cognitive radio network. Based on an online learning framework, we propose an algorithm to efficiently combine the individual sensing results based on the past performance of each detector. Additionally, we show how to utilize the learned normalized weights as a proxy metric of detection accuracy and selectively enable the sensing at detectors. Our results show improved performance in terms of inter-user collision and misdetection. Further, by selectively enabling some of the devices in the network, we propose a strategy to extend the field life of devices without compromising on detection accuracy.

中文翻译：

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在节俭的物联网网络中利用 CSS 的在线学习

我们提出了一种利用认知无线电网络的物联网网络集中协作频谱感知的新方法。基于在线学习框架，我们提出了一种算法，可以根据每个检测器的过去性能有效地组合各个传感结果。此外，我们展示了如何利用学习到的归一化权重作为检测精度的代理指标，并有选择地启用检测器的感知。我们的结果显示在用户间冲突和误检测方面的性能有所提高。此外，通过选择性地启用网络中的某些设备，我们提出了一种策略，可以在不影响检测精度的情况下延长设备的现场寿命。