Performance Analysis of Energy Harvesting Cognitive Radion Network

The spectral utilization and energy efficiency are two key factors that are predominantly driving the future of wireless communication. Cognitive Radio Network (CRN) along with energy harvesting is an encourage ing solution to overcome spectrum under-utilization and energy paucity. A cooperative CRN to analyzed energy harvesting and throughput on the basis of prediction based sensing mechanism under OR fusion rule. Prediction based sensing enhance the spectrum utilization and protects the quality of service (QOS) of primary user (PU). Cognitive Radio (CR) harvests energy from radio frequency (RF) source and non-RF source based on combined decision of fusion center. Based on combined decision declared by the FC the CRN harvest energy either from RF or non-RF sources. When combined decision declares that PU is absent then only CR node starts transmission. The role of distribution function on performance of such model is wide. We introduc Weibull distribution and Erlang distribution function in characterizing the primary user activity and analyze the performance of several parameters. An analytical expression for detection probability, false alarm probability, energy harvesting, normalize throughput and energy penalty are derived.