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Online Maneuver Design for UAV-Enabled NOMA Systems via Reinforcement Learning
arXiv - CS - Information Theory Pub Date : 2019-08-12 , DOI: arxiv-1908.03984
Yuwei Huang, Xiaopeng Mo, Jie Xu, Ling Qiu, Yong Zeng

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.

中文翻译:

通过强化学习为支持无人机的 NOMA 系统进行在线机动设计

本文考虑了一种无人机启用上行链路非正交多址系统,其中地面上的多个移动用户通过非正交多址传输向空中的无人机发送独立的消息。我们的目标是设计无人机动态机动,以在有限的时间范围内最大化所有移动地面用户的总速率吞吐量。
更新日期:2020-01-22
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