Maximizing throughput of aerial base stations via resources-based multi-agent proximal policy optimization: A deep reinforcement learning approach

YM Park, SS Hassan, CS Hong - 2022 23rd Asia-Pacific …, 2022 - ieeexplore.ieee.org
Fifth-generation (5G) networks use millimeter-wave (mmWave) technology to process high-
speed and capacity data services. However, wireless communication losses occur due to …
被引用次数：2 相关文章

Maximizing Throughput of Aerial Base Stations via Resources-based Multi-Agent Proximal Policy Optimization: A Deep Reinforcement Learning Approach

YM Park, SS Hassan, CS Hong - 23rd Asia-Pacific Network …, 2022 - khu.elsevierpure.com
Abstract Fifth-generation (5G) networks use millimeter-wave (mmWave) technology to
process high-speed and capacity data services. However, wireless communication losses …

Maximizing Throughput of Aerial Base Stations via Resources-based Multi-Agent Proximal Policy Optimization: A Deep Reinforcement Learning Approach

YM Park, SS Hassan, CS Hong - IEICE Proceeding Series, 2022 - cir.nii.ac.jp
抄録 Fifth-generation (5G) networks use millimeter-wave (mmWave) technology to process
high-speed and capacity data services. However, wireless communication losses occur due …

Maximizing Throughput of Aerial Base Stations via Resources-based Multi-Agent Proximal Policy Optimization: A Deep Reinforcement Learning Approach

YM Park, SS Hassan, CS Hong - IEICE Proceedings Series, 2022 - ieice.org
Fifth-generation (5G) networks use millimeter-wave (mmWave) technology to process high-
speed and capacity data services. However, wireless communication losses occur due to …

Maximizing Throughput of Aerial Base Stations via Resources-based Multi-Agent Proximal Policy Optimization: A Deep Reinforcement Learning Approach

YM Park, SS Hassan, CS Hong - IEICE Proceedings Series, 2022 - ieice.org
Fifth-generation (5G) networks use millimeter-wave (mmWave) technology to process high-
speed and capacity data services. However, wireless communication losses occur due to …