Multi-agent reinforcement learning based 3D trajectory design in aerial-terrestrial wireless caching networks

This paper investigates a dynamic 3D trajectory design of multiple cache-enabled unmanned aerial vehicles (UAVs) in a wireless device-to-device (D2D) caching network with the goal of maximizing the long-term network throughput. By storing popular content at the nearby mobile user devices, D2D cachin...

Full description

Saved in:
Bibliographic Details
Main Authors: Yu-Jia Chen, Kai-Min Liao, Meng-Lin Ku, Fung Po Tso, Guan-Yi Chen
Format: Default Article
Published: 2021
Subjects:
unmanned aerial vehicles (UAVs)
trajectory design
wireless caching
multi-agent reinforcement learning
Online Access:https://hdl.handle.net/2134/14892744.v1
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://hdl.handle.net/2134/14892744.v1

Similar Items