Performance of Weibull Distribution Function on Prediction Based EH-CRN with Diverse Fusion

Abstract

Reduction of energy footprint and spectral underutilization are the two major challenges for communication technology. Energy harvesting (EH) enabled cooperative cognitive radio network (CRN) promises to address this pertinent issue and aspires to play the pivotal role in driving future wireless communication. The distribution function plays an important role on the performance of such model. In this paper, we introduced Weibull distribution function in characterizing the primary user activity and analyzed the performance of various parameters of a cooperative CRN with energy harvesting capability under various fusion rules. The transition between idle and busy state of a CR is modeled as two state Markov model. In this model, a CR can harvest energy either from radio frequency (RF) source or from non-RF source based on combined decision of the fusion center (FC). Impact of prediction based sensing, number of cooperative cognitive radio (CR) nodes, collision constraint, number of frames, splitting parameter on throughput performance and energy harvesting are examined. Analytical expression for detection probability, false alarm probability, improvement in spectrum reuse, harvested energy, energy penalty and normalize throughput are established. A comprehensive simulation of the system model is performed and the results are compared for various fusion rules in a cooperative EH-CRN.

Keywords: Cognitive radio, cooperative network, energy harvesting, fusion rules, throughput, Weibull distribution

Cite this Article: Banani Talukdar, Deepak Kumar, Sanjoy Debnath, Wasim Arif. Performance of Weibull Distribution Function on Prediction based EH-CRN with Diverse Fusion. International Journal of Distributed Computing and Technology. 2020; 6(1): 35–47p.