LAUSR

We analyze a Cognitive Radio-based Internet-of-Things (CR-IoT) network employing Microwave Power Transfer (MPT) method for energy-harvesting, targeted for smart city applications. In our model, multiple IoT sensors, operated by an IoT operator, coexist with a Primary Network Provider (PNP), where the IoT sensors opportunistically exploit the spectrum holes in the PNP’s licensed band. We develop an Imbedded Markov Chain based approach to analyze this system. During PNP’s inactivity periods, the Accesss Points (APs) under the IoT operator have to judiciously use PNP’s licensed band for data collection from the IoT sensors and charging them via the MPT method. Our analysis finds the balance between these activities while maintaining the Quality-of-Service and preventing energy deficit in the IoT sensors. We characterize PNP’s activity using any distribution, rather than exponential distribution used in literature, making our framework more accurate. We also consider the possibility of interruptions in the IoT operator’s activity due to PNP’s transmission, which has been overlooked in the literature. Extensive simulations demonstrate the accuracy of our analysis. Our analysis can identify the values of system parameters that makes the system sustainable. We have also shown how to extend our model to accommodate multiple PNPs in the same CR-IoT network.