Fairness-Based User Scheduling and Performance Optimization in Energy Harvesting Cognitive Network

In this work we consider a cognitive radio network with a energy harvesting relay that facilitates coexistence between primary users and multiple secondary users (SU) and a secondary destination. We analyze the outage performance of this cognitive radio network that employs a decode-and-forward (DF) relay and harvests energy from the secondary user’s transmitted signal. Cumulative distribution function-based user scheduling is performed for equitable allocation of channels to each SU. We consider block Rayleigh fading channels and derive novel closed-form expressions for the outage probability and system throughput. Monte Carlo simulations are conducted to verify the accuracy of the outage expression. We also develop the expression for the outage probability at a high interference threshold and utilize it to examine the impact of the power splitting factor (α) on overall performance. Our results demonstrate that through using an optimum power splitting factor the outage performance can be enhanced by nearly 2 dB.