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Deep Reinforcement Learning Assisted Beam Tracking and Data Transmission for 5G V2X Networks

February 6, 2023

Author(s)

Junliang Ye, Hamid Gharavi

Beam tracking is a core issue in 5G vehicle-to-everything (V2X) networks. Specifically, higher beamforming gain is required to compensate for the path loss at higher frequencies, e.g., 5G FR2, to realize high data rate vehicle-to-infrastructure (V2I)

Deep reinforcement learning assisted energy harvesting wireless networks

May 24, 2021

Author(s)

Junliang Ye, Hamid Gharavi

Heterogeneous ultra-dense networking (HUDN) with energy harvesting technology is a promising approach to deal with the ever-growing traffic that can severely impact the power consumption of small-cell networks. Unfortunately, the amount of harvested energy