Joint Optimization of Energy Harvesting and Detection Threshold for Energy Harvesting Cognitive Radio Networks

Abstract

Spectrum efficiency and energy efficiency are two critical issues in the design of wireless communication networks. Recently, energy harvesting cognitive radio networks have been proposed to attempt to solve both the issues simultaneously. In this paper, we consider a cognitive radio network in which a primary transmitter mainly occupies the channel, and a secondary transmitter equipped with an energy harvesting device is allowed to opportunistically access the primary channel at any time if it is detected to be idle. Here, we assume that energy arrival process and primary channel state are random process and two-state time-homogenous discrete Markov process, respectively. Instead of the expected number of successful spectrum access attempts per time slot as a design criterion in current literature, we use the average channel capacity as the achievable throughput to jointly optimize energy harvesting and spectrum sensing subject to the constraints on the energy causality, collision, and temporal correlation of probability of sensing the idle/occupied channel, thus achieving or almost achieving both the energy efficiency and the spectrum efficiency in certain conditions. In addition, the corresponding optimum detection threshold and the maximum achievable throughput are obtained, which are substantiated by our comprehensive computer simulations.