Deep Reinforcement Learning Based JointDownlink Beamforming ...

Deep Reinforcement Learning Based Joint Downlink Beamforming ...

We introduce a novel deep reinforcement learning (DRL) approach to jointly optimize transmit beamforming and reconfigurable intelligent surface (RIS) phase ...

Deep Reinforcement Learning Based Joint Downlink Beamforming ...

Deep Reinforcement Learning Based Joint. Downlink Beamforming and RIS Configuration in. RIS-aided MU-MISO Systems Under Hardware. Impairments and Imperfect CSI.

Deep Reinforcement Learning Based JointDownlink Beamforming ...

Abstract [en] ... Our numerical results show that the introduced framework substantially outperforms the vanilla DRL agent under mismatch and ...

baturaysaglam/RIS-MISO-PDA-Deep-Reinforcement-Learning

... Deep Reinforcement Learning Based Joint Downlink Beamforming and RIS Configuration in RIS-Aided MU-MISO Systems Under Hardware Impairments and Imperfect CSI ...

Deep Reinforcement Learning Based Joint Downlink Beamforming ...

Request PDF | On May 28, 2023, Baturay Saglam and others published Deep Reinforcement Learning Based Joint Downlink Beamforming and RIS Configuration in ...

Deep Reinforcement Learning Enabled Joint Deployment and ...

Deep reinforcement learning based joint downlink beamforming and ris configuration in ris-aided mu-miso systems under hardware impairments and imperfect csi.

Deep Reinforcement Learning based Joint Active and Passive ...

However, the joint active beamforming and passive beamforming design is an arduous task due to the high computational complexity and the dynamic ...

Machine Learning for User Partitioning and Phase Shifters Design in ...

Deep Reinforcement Learning Based Joint Downlink Beamforming and RIS ... deep reinforcement learning approach to jointly optimize transmit beamforming ...

Impact of memory on beamforming optimization for DDPG-assisted ...

Saglam B, Gurgunoglu D, Kozat SS (2022) Deep Reinforcement Learning Based Joint Downlink Beamforming and RIS Configuration in RIS-aided MU ...

Deep Reinforcement Learning-Based Coordinated Beamforming for ...

In this paper, we propose a novel deep reinforcement learning (DRL) based coordinated beamforming scheme where multiple base stations serve one mobile station ...

GitHub - ken0225/RIS-Codes-Collection

Guo, etal. 65, Deep Reinforcement Learning Based Joint Downlink Beamforming and RIS Configuration in RIS-aided MU-MISO Systems Under Hardware Impairments and ...

Deep Reinforcement Learning-Based Coordinated Beamforming for ...

Deep Reinforcement Learning-Based Coordinated Beamforming for mmWave Massive MIMO Vehicular Networks. Sensors (Basel). 2023 Mar 3;23(5):2772. doi: 10.3390/ ...

A deep reinforcement learning based framework for power-efficient ...

This paper proposes a joint downlink (DL) and UL MU-AP association and beamforming design to coordinate interference in the C-RAN for energy minimization ...

Deep reinforcement learning-based beam training with energy and ...

2 Machine learning-based beam training techniques. Recently, machine learning (ML) algorithms have drawn lots of attention in wireless ...

Deep Reinforcement Learning-Based Adaptive Beam Tracking and ...

In this paper, we propose a novel switched beam antenna system model integrated with deep reinforcement learning (DRL) for 6G ...

Deep Reinforcement Learning-Based Optimization for RIS-Based ...

... beamforming for a 2-user RIS-UAV-NOMA downlink system. Most RIS-related works consider only fixed channel environments. However, the time-varying multi-user ...