… reinforcement learning (DRL) and propose a distributed dynamic downlink-beamforming …
On the other hand, downlink beamforming technique has also attracted considerable attention …

… method for mmWave beamforming in massive multiple-input … In doing so, we utilize deep
reinforcement learning (DRL) to … (UE) and obtain its hybrid beamforming matrices. In doing so, …

… propose a beamforming framework that exploits multi-agent deep reinforcement learning (…
We propose to maximize the system downlink sum-rate by jointly optimizing the beamforming …

… channel prediction and downlink beamforming schemes, rather than … beamforming matrix,
while the beamforming gain depends on the accuracy of the predicted CSI. Thus, the learning …

… learning based algorithm based on a reinforcement learning (RL… The importance of
reinforcement learning in power control … ×1 denote the adopted downlink beamforming vectors at …

… propose a deep learning framework for the optimization of downlink beamforming. In particular,
… to measure errors in machine learning regression algorithms,” Interdiscipl. J. Inf., Knowl. …

… network, simultaneous uplink/downlink beamforming within a … tasks of an uplink/downlink
cell-free network becomes more … -free networks focuses on uplink/downlink beamforming [3], [8…

… learning method to solve this problem with perfect downlink CSI. However, without downlink
CSI H𝐷, existing numerical or deep learning … design of downlink beamforming algorithms, …

… beamforming for millimeter wave massive multiple-input multiple-output (MIMO) system based
on deep reinforcement learning … Consider a mmWave massive MIMO single-user downlink …

… a deep reinforcement learning (DRL)-based scheme of downlink beamforming and phase
… control the beamforming and phase shift, respectively. Further, a DDPG-based distributed …