Deep Reinforcement Learning-Based Joint Routing and Capacity Optimization in an Aerial and Terrestrial Hybrid Wireless Network

Deep Reinforcement Learning-Based Joint Routing and Capacity Optimization in an Aerial and Terrestrial Hybrid Wireless Network

As the airspace is experiencing an increasing number of low-altitude aircraft, the concept of spectrum sharing between aerial and terrestrial users emerges as a compelling solution to improve the spectrum utilization efficiency. In this paper, we consider a new Aerial and Terrestrial Hybrid Network...

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Bibliographic Details
Main Authors: Zhe Wang, Hongxiang Li, Eric J. Knoblock, Rafael D. Apaza
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
ATHN
packet routing
E2E delay
capacity
DRL-based algorithm
D3QN
Online Access:https://ieeexplore.ieee.org/document/10600704/
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https://ieeexplore.ieee.org/document/10600704/

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