As technology advances in recent years and the emergence of the widespread applications in the field of wireless communications, the number of wireless equipments has increased considerably. The supply of energy for a large number of wireless equipments has become a major challenge in scientific and industrial communities, specifically, in applications where access to the wireless equipments are difficult and even impossible. Using wireless power transfer WPT technology, and energy harvesting by wireless equipments has led to the creation of a useful and cost-effective solution in the wireless communications industry. The advancement of the science in the antenna and semiconductor fields has increased the efficiency of the wireless power transmission and the energy harvesting, resulting in increase of using this technology. On the other hand, the limitation of the capacity of the wireless equipments batteries in the wireless powered communication networks WPCN has led to the issue of optimal energy use in these networks. The aim of achieving the desired quality of service (QoS) and optimal energy consumption together led to the emergence of the concept of energy efficiency in wireless powered communication networks. Due to the high importance of energy efficiency in wireless powered communication networks, this study attempts to improve the network energy efficiency by simultaneously optimizing both time and power. In fact, the main purpose of this research is to maximize the energy efficiency function by considering the quality of service, fairness, limiting the capacity of the equipments battery, and causality of the energy system. Also, in order to improve the network energy efficiency, we use the users information signal for energy harvesting process. In this study, we show that the network energy efficiency function is non-convex. Then, using the nonlinear fractional programming theory, and also the change of the variables, we transform the objective function into a convex function. Then, using the Dinkelbach algorithm, we will simulate the optimization problem in the MATLAB software. Also we show that using the user's information signal as an energy source will improve energy efficiency of network. Resource Allocation for Wireless Powered Communication Networks for Energy Efficiency Improvement