Deep Reinforcement Learning-Based Scheduling for Multiband Massive MIMO

被引：0

作者：

Lopes, Victor Hugo L. ^{[1
,2
]}

Nahum, Cleverson Veloso ^{[3
]}

Dreifuerst, Ryan M. ^{[4
]}

Batista, Pedro ^{[5
]}

Klautau, Aldebaro ^{[3
]}

Cardoso, Kleber Vieira ^{[1
]}

Heath, Robert W. ^{[6
]}

机构：

[1] Institute of Informatics, Federal University of Goiás, Goiânia,74690-900, Brazil

[2] Federal Institute of Education, Science, and Technology of Goiás, Inhumas,75402 556, Brazil

[3] Federal University of Pará, Department of Computer and Telecommunication Engineering, Belém,66075-110, Brazil

[4] The University of Texas at Austin, Wireless Networking and Communications Group, Austin,TX,78712, United States

[5] Ericsson Research, Stockholm,164 83, Sweden

[6] North Carolina State University, Department of Electronics and Computer Engineering, Raleigh,NC,27606, United States

来源：

IEEE Access | 2022年 / 10卷

关键词：

Deep reinforcement learning-based scheduling - Mm waves - Multi band - Multiband scheduling - Multiple inputs - Multiple outputs - Multiple-input-multiple-output - Packets loss rate - Reinforcement learning agent - Reinforcement learnings;

D O I：

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摘要：

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页码：125509 / 125525

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