Abstract

This paper presents a new three-dimensional (3D) trajectory design approach for a solar-powered, fixed-wing unmanned aerial vehicle (UAV) to harvest solar energy and collect data from multiple smart devices (SDs). The trajectory is optimized based on max-min fairness to balance the total amount of uploaded data and the fairness among the SDs. The key idea is that we develop non-trivial variable substitution and successive convex approximation (SCA) techniques to convexify data transmission, UAV energy consumption and mobility, and energy harvesting constraints under a persistent round-robin transmission schedule of the SDs. The resulting algorithm guarantees a locally optimal trajectory satisfying the Karush-Kuhn-Tucker (KKT) conditions. Another important aspect is that we further jointly optimize the transmission schedule along with the trajectory, and prove that absolute fairness in terms of uploaded data can be achieved among the SDs under the max-min fairness. The new algorithms apply to both line-of-sight (LoS)-dominant and probabilistic SD-UAV channels. Numerical results show that a 3D trajectory increases the uploaded data by 111%, compared to a two-dimensional (2D) trajectory. The proposed algorithms can balance the energy harvesting and data collection, and achieve fairness in both LoS-dominant and probabilistic SD-UAV channels.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call