Genetic Algorithm-Based Hybrid Spectrum Handoff Strategy in Cognitive Radio-Based Internet of Things

Abstract In Cognitive radio-based Internet of Things (CR-IoT) systems, the return of the primary user (PU) causes the secondary user (SU) that is communicating to face the spectrum handoff problem. In the process of spectrum handoff, the user terminal can’t get the idle channels in time because of the unknown channel usage state. To solve this problem, a hybrid spectrum handoff algorithm based on the channel idle probability is proposed. The algorithm considers the regularity of PU activities in space and time, defines the idle probability of channels from the perspective of week attributes and time periods, obtains the optimal time period length using genetic algorithm, generates a channel idle probability table, and provides the target channel sequence for SUs in combination with the proposed channel ordering scheme. Simulation results show that the hybrid spectrum switching algorithm based on the channel idle probability can reduce the energy consumption of SUs during spectrum switching, reduce the communication interruption rate, enable SUs to find idle channels faster and reduce the number of sensing times.