Energy efficient sensing with spectrum opportunity forecasting for cognitive radio networks

Energy efficiency and adaptability in the utilization of radio spectrum are two major research challenges for the advancement of future wireless communications technologies. To address these difficulties, we enhance the energy efficiency by utilizing spectrum opportunity forecasting (SOF) and optimal scheduling for sensor node activation to decrease the required number of SS events. The application of SOF to cooperative spectrum sensing (SS) is one of the exceptional commitments of this paper. Results demonstrated that this combination could significantly diminish sensor node energy utilization and in this manner increase cognitive radio network (CRN) lifetime. A positive direct relationship was found between forecast length and CRN lifetime. A vast change in the collective lifetime of the sensor system was observed when SOF was utilized for a forecast length of ten SS events, utilizing implicit enumeration (IE) under the uniform sensor node distribution.