Modelling and performance analysis of RF energy harvesting cognitive radio networks

Abstract

RF energy harvesting cognitive radio (RF-EH-CR) networks are becoming increasingly important. Channel selection schemes for spectrum sensing play an important role towards increasing the throughput of the secondary users in cognitive radio networks. In this paper, with the help of simulations, we show that the ‘modified myopic EH’ scheme put forth by us performs better than other channel selection schemes and obtains throughput close to complete information case in RF-EH-CR network. The effect of packet arrival probability, energy harvesting probability and the probability of channel availability on the throughput of secondary users using ‘modified myopic EH’ scheme is also discussed. Using Markov chain analysis, we computed the packet drop probability for a secondary user with limited packet and energy buffer. The effect of packet arrival probability and channel availability on the packet drop is also discussed.