Green-Energy-Powered Cognitive Radio Networks

Abstract

This article studies a green-energy-powered cognitive radio network (GCRN) in an underlay paradigm, wherein multiple battery-free secondary users (SUs) capture both the spectrum and the energy of primary users (PUs) to communicate with an access point (AP). By time division multiple access, each SU transmits data to AP in the allocated time and harvests energy from the RF signals of PUs otherwise, all in the same licensed spectrum concurrently with PUs. Thus, the transmit power of each SU is jointly constrained by the peak interference power at PU and the harvested energy of SU. With the formulated green coexistence paradigm, we investigate the sum-throughput maximization problem with respect to time and power allocation, which is non-convex. To obtain the optimal resource allocation, we propose a joint optimal time and power allocation (JOTPA) algorithm that first transforms the original problem into a convex optimization problem with respect to time and energy allocation, and then solve it by iterative Lagrange dual decomposition. To comprehensively evaluate the performance of the GCRN with JOTPA, we deploy the GCRN in three typical scenarios and compare JOTPA with the equal time and optimal power allocation (ETOPA) algorithm. Extensive simulations show that the deployment of the GCRN significantly influences the throughput performance and JOTPA outperforms ETOPA under all considered scenarios.