Efficient Channel Allocation for Cognitive Radio Internet of Things

Abstract

Recently, multiple wireless technology has arisen to provide effective and flexible IoT networking. Cognitive radio (CR) technology that facilitates software-defined radio is one of the key technology that gives IoT connectivity to a multitude of linked IoT devices in an opportunistic way. Unlicensed bandwidth has congested latest creation and study in the area of networking technology. The effect is unchecked and unregulated intrusion in the Internet of Things with low-powered wireless sensors (IoT). On the other hand, these technologies allowed low-energy IoT architecture at low cost, low energy usage and efficient spectrum use. Cognitive radio (CR) network, a low-cost approach for effective spectrum use, discusses the issue of spectrum use. Unlicensed users use underused bandwidth in CR networks. Due to its opportunistic existence, these networks' output relies on the observed spectrum pattern of the primary consumer. In these networks, frequency detection and usage must be accurately modelled. In this article, we propose the main Cognitive Radio Internet of Things (CR IoT) user identity mechanism using Markov's secret model. We implemented two algorithms: one for free channel identification and one for successful channel allocation. Simulation results suggest that CR-IoT surpassed traditional networking systems.