  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.
