Joint Power Control and UAV Trajectory Design for Information Freshness via Deep Reinforcement Learning

Research article (2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring), 2022) · cited 10× · AI/ML
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Joint Power Control and UAV Trajectory Design for Information Freshness via Deep Reinforcement Learning

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Joint Power Control and UAV Trajectory Design for Information Freshness via Deep Reinforcement Learning is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Joint Power Control and UAV Trajectory Design for Information Freshness via Deep Reinforcement Learning. Retrieved May 24, 2026, from https://4ort.xyz/entity/joint-power-control-and-uav-trajectory-design-for-information-freshness-via-deep-reinforcement-learning
MLA “Joint Power Control and UAV Trajectory Design for Information Freshness via Deep Reinforcement Learning.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/joint-power-control-and-uav-trajectory-design-for-information-freshness-via-deep-reinforcement-learning.
BibTeX @misc{4ortxyz_joint-power-control-and-uav-trajectory-design-for-information-freshness-via-deep-reinforcement-learning_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Joint Power Control and UAV Trajectory Design for Information Freshness via Deep Reinforcement Learning}}, year = {2026}, url = {https://4ort.xyz/entity/joint-power-control-and-uav-trajectory-design-for-information-freshness-via-deep-reinforcement-learning}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Joint Power Control and UAV Trajectory Design for Information Freshness via Deep Reinforcement Learning — https://4ort.xyz/entity/joint-power-control-and-uav-trajectory-design-for-information-freshness-via-deep-reinforcement-learning (retrieved 2026-05-24)

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