## 1 Introduction  
Wireless sensor networks collect and exchange data via the interconnection between heterogeneous devices, and such networks are widely applied in intelligent logistics, smart cities, disasters, and so on [1, 2]. The third and fourth generations of mobile communication technology (3G and 4G) are excellent infrastructures for supporting Internet of Things (IoT) due to the wide coverage, low deployment cost, and high security. However, it is difficult to achieve the high data rate, low latency, and low power consumption for physical communication. Fortunately, the Internet of Everything has been made possible by the advent of 5G technology, which provides connected devices with gigabit data rates and low-latency communications. The 5G-enabled WSN has consequently attracted a lot of attention from the industry and academia [3, 4, 5, 6, 7]. In fact, wireless sensor networks connect a large number of devices that consume huge amounts of power, making the lifetime of the battery a bottleneck for network performance. Energy harvesting (EH) and wireless power transfer (WPT) can be regarded as promising technologies that are able to extend a battery's lifetime. The former absorbs energy from wind and solar but is less sustainable. Typical technologies for wireless power transfer include inductively coupled charging and electromagnetic magnetic resonance coupling, both of which can transfer power to distances ranging from centimeters to meters but not over longer distances. The wireless power transfer supported by radio frequency technology belongs to far field charging, which can transfer energy several kilometers away. Therefore, radio frequency wireless power transfer (RF-WPT) has aroused great interest in the research community and industry. Static charger is the main implementation of RF-WPT, while the disadvantage of this is that it will cause a waste of energy, and it is difficult to satisfy the various energy requirements [8; 9; 10]. One way to fix it is to employ a ground mobile charger to replenish the sensor devices (SDs). However, the drawbacks are also obvious. The path planning and communication quality of ground mobile chargers are susceptible to the terrain, and therefore it is difficult to replenish energy efficiently and to do so in a timely way [11; 12; 13; 14; 15; 16; 17]. Compared with mobile charging vehicles on the ground, UAVs have advantages of rapid deployment and high communication quality, which are particularly suitable for deployment in rural and harsh environment regions. Not only does the UAV power the SDs, but it also enables air-to-ground communication via an onboard wireless transceiver, allowing data to be collected from a wider area at a faster rate. Consequently, it is feasible to use the UAVs equipped with RF-WPT to improve the performance of wireless network [18; 19; 20]. Specifically, a UAV is assigned a preset the trajectory to visit SDs distributed across the target area. When hovering over a SD, the downlink provides wireless charging to the SD, while the uplink provides data transmission services. The mobility of the UAV enables easy access to SDs; however, limited capacity makes it difficult for a single UAV to perform charging and communication tasks in a large-scale network, and hence it is necessary to deploy multiple UAVs at the same time. In addition, the generated status information needs to be delivered to the destination as quickly as possible for online data analysis and decision making, and outdated information may lead to false control or even major disasters. Therefore, on the one hand, information collection delay needs to be limited to a short period. On the other hand, the energy efficiency of UAVs should be improved as much as possible, that is to say, to replenish more energy for SDs. They are two conflicting objectives that need to be considered jointly.