A dynamic energy efficient cooperative spectrum allocation for cognitive radio based internet of things networks

Abstract

The Cognitive Radio Network (CRN) is a promising and intelligent newlinewireless technology that facilitates the detection of the state of the newlinecommunication channels which are in use. The channel spectrum is pre newlineallocated for the licensed users (Primary Users). The unlicensed users newline(Secondary Users) can efficiently utilize the spectrum spaces of the licensed newlineusers without imposing any interference to them. The spectrum sensing is the newlinekey aspect of CRN that makes intelligent decisions by continuously monitoring newlinethe spectral patterns of Primary User (PU) activity. The quality of spectrum newlinesensing needs more importance while implementing CRN in real time scenarios newlinelike M2M communications, Internet of Things (IoT) applications, and so on. newlineThe primary goal of this thesis is to address the issues prevalent in spectrum newlinesensing mechanism mainly the trade-off between sensing time and transmission newlinetime. The incentive-based optimization algorithm for optimizing the sensing newlinetime and transmission time is introduced in order to maximize the energy newlineefficiency and throughput for the considered CRN ensuring quality data newlinetransmission. The probability of detection (and#119875;and#119889;) and the probability of false newlinealarm (and#119875;and#119891;and#119886;) are used to measure the accuracy of spectrum sensing process . The newlineoptimised values of the sensing time and transmission time shows 14% newlineimprovement over the sub optimal algorithm enabling successful data newlinetransmission. The proposed work also contributes to a significant increase in newlineenergy efficiency with minimal interference. The simulation results show 3.5% newlineincrease in energy efficiency and throughput when compared with the existing newlinealgorithms. newline