Deep Reinforcement Learning Based Resource Allocation for V2V Communications

In this paper, we develop a novel decentralized resource allocation mechanism for vehicle-to-vehicle (V2V) communications based on deep reinforcement learning, which can be applied to both unicast and broadcast scenarios. According to the decentralized resource allocation mechanism, an autonomous &q...

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Vydané v:	IEEE transactions on vehicular technology Ročník 68; číslo 4; s. 3163 - 3173
Hlavní autori:	Ye, Hao, Li, Geoffrey Ye, Juang, Biing-Hwang Fred
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.04.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Deep learning Deep Reinforcement Learning Interference Optimization Reinforcement learning Reliability Resource Allocation Resource management Unicast V2V Communication Vehicle-to-infrastructure Vehicular ad hoc networks
ISSN:	0018-9545, 1939-9359
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