# Optimal Charging Profile Design for Solar-Powered Sustainable UAV Communication Networks

arXiv: https://arxiv.org/abs/2302.06092 · HTML: https://mlsanity.com/paper/2302.06092/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Feb 2023.

## Built on by (most cited first, 1 of 1)

- [Learning with Dynamics: Autonomous Regulation of UAV Based Communication Networks with Dynamic UAV Crew](https://mlsanity.com/paper/2409.17139/) (2024)

## Abstract (arXiv)

This work studies optimal solar charging for solar-powered self-sustainable UAV communication networks, considering the day-scale time-variability of solar radiation and user service demand. The objective is to optimally trade off between the user coverage performance and the net energy loss of the network by proactively assigning UAVs to serve, charge, or land. Specifically, the studied problem is first formulated into a time-coupled mixed-integer non-convex optimization problem, and further decoupled into two sub-problems for tractability. To solve the challenge caused by time-coupling, deep reinforcement learning (DRL) algorithms are respectively designed for the two sub-problems. Particularly, a relaxation mechanism is put forward to overcome the "dimension curse" incurred by the large discrete action space in the second sub-problem. At last, simulation results demonstrate the efficacy of our designed DRL algorithms in trading off the communication performance against the net energy loss, and the impact of different parameters on the tradeoff performance.