Distributed Safe Multi-Agent Reinforcement Learning: Joint Design of THz-Enabled UAV Trajectory and Channel Allocation

6G is anticipated to play a foundational role in realizing various emerging entertainment applications and critical societal services, such as smart agriculture, public safety, and so on. Providing the underlying communications for these applications will substantially increase demand for data rate,...

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Vydáno v:	IEEE transactions on vehicular technology Ročník 73; číslo 10; s. 14172 - 14186
Hlavní autoři:	Termehchi, Atefeh, Syed, Aisha, Kennedy, William Sean, Erol-Kantarci, Melike
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.10.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	6G mobile communication Algorithms Autonomous aerial vehicles Band theory Collision avoidance Constraints Deep learning Energy efficiency Internet of Things Mixed integer multi-agent deep reinforcement learning Multiagent systems Nonlinear programming Optimization Public safety Quality of service architectures Reliability resource allocation Safe learning Safety Terahertz communications THz-enabled UAVs Trajectory trajectory design Unmanned aerial vehicles
ISSN:	0018-9545, 1939-9359
On-line přístup:	Získat plný text
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