Throughput Maximization With Energy Harvesting in UAV-Assisted Cognitive Mobile Relay Networks

In order to extend the communication coverage and improve system performance, the applications of unmanned aerial vehicles (UAVs) in wireless communications have attracted a lot of attention in the industry. In this paper, we propose a power control algorithm in energy harvesting (EH)-based cognitive mobile relay networks where an UAV is equipped with a decode-and-forward (DF) relay to cooperate the communication of secondary user (SU). Assuming that the only power source for SU transmitter with EH is a battery with infinite capacity, we solve a throughput maximization problem to optimize the transmit powers of SU and the mobile relay, subject to the causality constraint of energy usage at SU transmitter, the maximum transmit power constraint of the mobile relay, and the interference temperature (IT) constraint to protect the communication of primary user (PU). When formulating this throughput maximization problem, we adopt an offline scheme with deterministic settings. For simplicity, the original multi-variable optimization problem is transformed into a single variable optimization problem via the optimal throughput principle of the DF relaying communication system. Furthermore, we solve this new optimization problem via the Lagrange dual method, and we derive the closed-form expressions of the optimal solutions. The simulation results illustrate the optimized system performance that the optimal throughput of the secondary system can be achieved by the proposed dynamic power control algorithm.