Trajectory design and transmission optimization for data freshness in UAVs-assisted WPCNs

To address the issues of energy supply and data freshness in the wireless powered communication network (WPCN), the long-term average age of information (AoI) in an unmanned aerial vehicles (UAVs)-assisted WPCN is investigated, where UAVs, fully charged by hybrid access points (HAPs), fly to the hovering points of islands to charge sensor nodes (SNs) and receive data from them, and fly back to offload the received data to the HAPs. Subject to the battery capacity constraint of UAVs, the formulated AoI minimization problem is non-convex due to discrete variables such as the selected hovering points and continuous variables such as the transmit power of SNs. With geographic locations of HAPs, the WPCN is divided into three areas, and propose an AoI-based clustering algorithm to cluster islands for UAVs to traverse subject to the battery capacity constraint. As data freshness depends on the flight distance and hovering duration of the UAV, the flight distance and hovering duration-based selecting hovering points (FHSHP) algorithm is proposed to define the candidate area, where the UAV chooses among candidate hovering points to minimize AoI. The FHSHP algorithm narrows the range of candidate hovering points to choose from, and achieves better tradeoff between the flight distance and the hovering duration of the UAV. Numerical results verify the superiority of the proposed FHSHP algorithm compared with comparison algorithms, and show the impacts of network parameters on the average AoI.