# Online Maneuver Design for UAV-Enabled NOMA Systems via Reinforcement Learning

arXiv: https://arxiv.org/abs/1908.03984 · HTML: https://mlsanity.com/paper/1908.03984/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Aug 2019.

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

- [Responsive Regulation of Dynamic UAV Communication Networks Based on Deep Reinforcement Learning](https://mlsanity.com/paper/2108.11012/) (2021)

## Abstract (arXiv)

This paper considers an unmanned aerial vehicle enabled-up link non-orthogonal multiple-access system, where multiple mobile users on the ground send independent messages to a unmanned aerial vehicle in the sky via non-orthogonal multiple-access transmission. Our objective is to design the unmanned aerial vehicle dynamic maneuver for maximizing the sum-rate throughput of all mobile ground users over a finite time horizon.