- Deep Reinforcement Learning for 5G Networks🔍
- a Deep Reinforcement Learning approach for 5G NR mmWave ...🔍
- Deep Reinforcement Learning|Based Coordinated Beamforming for ...🔍
- Flexible Robust Beamforming for Multibeam Satellite Downlink ...🔍
- Deep Reinforcement Learning Based JointDownlink Beamforming ...🔍
- Deep Reinforcement Learning|Based Optimization for ...🔍
- Deep Reinforcement Learning|Based On|Off Analog Beamforming ...🔍
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Deep Reinforcement Learning|Based Downlink Beamforming and ...
Deep Reinforcement Learning for 5G Networks: Joint Beamforming ...
Deep Reinforcement Learning-based Beamforming ... A deep learning framework for the optimization of downlink beamforming is proposed based ...
a Deep Reinforcement Learning approach for 5G NR mmWave ...
Such meth- ods require beam sweeping and rely only on received signal power measurements if spatial multiplexing is not required. • non-codebook based (or ...
Deep Reinforcement Learning-Based Coordinated Beamforming for ...
In this paper, we use the assumption that the MS is equipped with only one antenna. Sensors 23 02772 g001 550. Figure 1. Downlink mmWave mMIMO ...
Flexible Robust Beamforming for Multibeam Satellite Downlink ...
We use the Soft Actor Critic (SAC) deep Reinforcement Learning (RL) method to learn robust precoding strategies without the need for explicit insights into ...
Deep Reinforcement Learning Based Joint Downlink Beamforming and RIS ... This letter offers a novel deep reinforcement learning (DRL) algorithm based ...
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 ...
Deep Reinforcement Learning-Based Optimization for ... - Frontiers
Deep Reinforcement Learning-Based Optimization for RIS-Based UAV-NOMA Downlink ... beamforming for a 2-user RIS-UAV-NOMA downlink system. Most RIS-related ...
Deep Reinforcement Learning-Based On-Off Analog Beamforming ...
2: A downlink MISO small cell network. phase shifting. In contrast, the other antenna elements are switched off and thus disconnected. This allows forming a.
Kim, and I. Lee, "Multi-Agent Deep Reinforcement Learning for Decentralized Multi-UAV Mobile Edge Computing Networks," ... Park, "Deep Learning-Based ...
A deep reinforcement learning for energy efficient resource ...
The approaches are based on Deep learning and Reinforcement learning. ... Joint beamforming and phase shift design in downlink UAV networks with IRS-assisted NOMA.
Local Observations-Based Energy-Efficient Multi-Cell Beamforming ...
Deep reinforcement learning for distributed dynamic MISO downlink-beamforming coordination[J]. IEEE Transactions on Communications, 2020,68(10): 6070-6085 ...
Joint Beamforming, Power Allocation, and Splitting Control for ...
By means of deep reinforcement learning to estimate future rewards of actions based on the reported information from the users served by the networks, we ...
Deep Reinforcement Learning for 5G Networks: Joint Beamforming ...
Jointly optimizing beamforming, power control, and interference coordination in a 5G wireless network to enhance the communication performance to end users ...
A Survey on Reinforcement Learning for Reconfigurable Intelligent ...
(2022). Deep Reinforcement Learning-Based Optimization for RIS-Based UAV-NOMA Downlink Networks (Invited Paper). Front. Signal Process., 2.
Deep Reinforcement Learning for Multi-user Massive MIMO with ...
The design of beamforming for downlink multi-user massive multi ... Leveraging this DRL-based framework, interference management is explored and ...
Deep Reinforcement Learning Based End-to-End Multiuser Channel ...
This document proposes deep reinforcement learning based algorithms for end-to-end channel prediction and beamforming in multi-user downlink systems. It ...
Radio Resource Allocation for 5g Network using Deep ... - IJRASET
... learning based algorithm based on a reinforcement learning (RL) framework. ... In Paper [8], the authors propose a deep learning-based beam management and ...
A DRL-based Hybrid Beamforming Design - arxiv-sanity
This letter offers a novel deep reinforcement learning (DRL) algorithm based on a location-aware imitation environment for the joint beamforming design in an ...
Hybrid IRS-Assisted Secure Satellite Downlink Communications
Hybrid IRS-Assisted Secure Satellite Downlink Communications: A Fast Deep Reinforcement Learning Approach. ... beamforming design for ...
Distributed Multi-Cell Multi-User MISO Downlink Beamforming ... - ZTE
... Downlink Beamforming via Deep Reinforcement Learning. ... To address this, we propose a distributed deep reinforcement learning (DRL) based ...