… In particular, we propose a distributional reinforcement learning (DRL) approach to model
the distribution function of the downlink rate, and, then, the IR reflection coefficient is optimized …

… significance of mm-wave to 5G wireless system is diminished without adequate HO control.
In this study, we propose a model for HO control based on the offline reinforcement learning (…

… ) communication is a growing area of communication with a … in millimeter wave (mmWave)
communication networks. The … Then, by leveraging tools from machine learning, specifically …

… tracking for mobile millimeter wave communication systems,” … tracking technique for millimeter
wave-band communications,” … learning for position-aided millimeter wave beam training,” …

… propagation characteristics of mm-Wave signals and their … , mm-Wave systems utilize
directional communication through … Despite the capacity gains promised by integrating mmWave, …

… training, in this paper we propose an environment sensing based beam training algorithm
via deep reinforcement learning… of the environment and learn required latent probability …

… HSR in mm-wave band to … mm-wave train-ground communication system. To improve the
RSP, we propose an effective RX beamforming scheme based on deep reinforcement learning …

… Millimeter-wave (mmWave) communication is a key technology of fifth generation wireless
… a deep reinforcement learning (DRL) approach to address this challenge. By learning the …

… To overcome these limitations, this paper develops a deep reinforcement learning framework
that learns how to optimize the codebook beam patterns relying only on the receive power …

… Abstract—In this letter, we investigate the hybrid beamforming for millimeter wave massive
multiple-input multiple-output (MIMO) system based on deep reinforcement learning (DRL). …