Spectrum Sensing and Allocation Strategy for IoT Devices Using Continuous-Time Markov Chain-Based Game Theory Model

Abstract

Spectrum sensingis a strategic technology in ascertaining idle spectrum in cognitive radio (CR)-based IoT networks. Adaptability, receptiveness, and accuracy are the steeplechases in the Internet-connected device networks because of the broad spectrum of applications and wide usage of them across the global. CR helps in dynamically allocating unlicensed frequency bands to the Internet of Things (IoT) devices there by providing effective utilization of spectral holes. This letter proposes a nonoperative game theoretic model to implement a spectrum-sensing mechanism and analyze the spectral usage rates of a CR-based IoT networks. The strategy for spectrum access and utilization is developed using a noncooperative game theory, and a utility function in terms of spectral usage rate is developed using the 2-D continuous-time Markov chain model. A utility function is designed to analyze the performance of the proposed algorithm in terms of mean arrival rate, average throughput, and mean delay as a function of increasing load. The results show that the system is consistent and scalable and enhances the detection performance in cognitive IoT networks.