Joint Trajectory Design and BS Association for Cellular-Connected UAV: An Imitation-Augmented Deep Reinforcement Learning Approach

This article concerns the problem of the trajectory design and base station (BS) association for cellular-connected unmanned aerial vehicles (UAVs). To support safety-critical functions, one primary requirement for UAVs is to maintain reliable cellular connectivity at every time instant during the f...

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Vydané v:	IEEE internet of things journal Ročník 9; číslo 4; s. 2843 - 2858
Hlavní autori:	Chen, Yu-Jia, Huang, Da-Yu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 15.02.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Antenna gain Antenna radiation patterns Artificial neural networks Cell association cellular networks Completion time Connectivity Deep learning deep reinforcement learning (DRL) Interference Machine learning Radio signals Safety critical Signal strength Signal to noise ratio Three-dimensional displays Trajectory trajectory design Trajectory optimization unmanned aerial vehicle (UAV) Unmanned aerial vehicles
ISSN:	2327-4662, 2327-4662
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