Energy efficiency maximization in UAV communication networks with nonlinear energy harvesting

Wireless power transfer (WPT) technology has great potential for future Internet of Things (IoT) application scenarios of energy -constrained unmanned aerial vehicle (UAV)-assisted communication. To fully obtain power multiplexing gain and improve spectral efficiency, this paper investigates nonorthogonal multiple access (NOMA)-based WPT-charging UAV communication networks, where a multi -antenna base station (BS) transmits radio frequency energy signals to UAVs, and UAVs harvest energy and send the data information back to the BS. Nevertheless, due to practical limitations and the difficulty of linear energy harvesting (EH) models to capture the end -to -end energy conversion of real EH circuits, the effects of nonlinear EH should be considered. Considering the great difference between nonlinear and linear EH models on the system energy efficiency (EE), the EE maximization problem is established by jointly optimizing multivariable. As the problem is nontrivial and nonconvex, we transform the original problem from sum -of -ratios form into an equivalent objective function in subtractive form, then solve it by Lagrange dual decomposition approach. The simulation results verify the feasibility of the proposed algorithm, and the EE gains are obtained compared with benchmarks when the nonlinear EH strategy is fully considered.