Multi-agent deep reinforcement learning based downlink beamforming in heterogeneous networks
We consider a heterogeneous network (HetNet), where multiple access points (APs) of
potentially different transmission capacities serve users simultaneously via beamforming in …
potentially different transmission capacities serve users simultaneously via beamforming in …
Distributed uplink beamforming in cell-free networks using deep reinforcement learning
The emergence of new wireless technologies together with the requirement of massive
connectivity results in several technical issues such as excessive interference, high …
connectivity results in several technical issues such as excessive interference, high …
Learning cooperative beamforming with edge-update empowered graph neural networks
Cooperative beamforming has been recognized as an effective approach to meet the
dramatically increasing demand of various wireless data traffics. Conventionally, the …
dramatically increasing demand of various wireless data traffics. Conventionally, the …
Distributed beamforming techniques for cell-free wireless networks using deep reinforcement learning
In a cell-free network, a large number of mobile devices are served simultaneously by
several base stations (BSs)/access points (APs) using the same time/frequency resources …
several base stations (BSs)/access points (APs) using the same time/frequency resources …
A machine learning approach for beamforming in ultra dense network considering selfish and altruistic strategy
C Sun, Z Shi, F Jiang - IEEE Access, 2020 - ieeexplore.ieee.org
Coordinated beamforming is very efficient at managing interference in ultra dense network.
However, the optimal strategy remains as a challenge task to obtain due to the coupled …
However, the optimal strategy remains as a challenge task to obtain due to the coupled …
Self-tuning sectorization: Deep reinforcement learning meets broadcast beam optimization
Beamforming in multiple input multiple output (MIMO) systems is one of the key technologies
for modern wireless communication. Creating appropriate sector-specific broadcast beams …
for modern wireless communication. Creating appropriate sector-specific broadcast beams …
Deep learning enabled optimization of downlink beamforming under per-antenna power constraints: Algorithms and experimental demonstration
This paper studies fast downlink beamforming algorithms using deep learning in multiuser
multiple-input-single-output systems where each transmit antenna at the base station has its …
multiple-input-single-output systems where each transmit antenna at the base station has its …
Beamforming and Resource Allocation in Multi-cell OFDMA Systems based on Deep Transfer Reinforcement Learning
G Sun, X Wang, R Jiang, Y Xu - 2022 IEEE 95th Vehicular …, 2022 - ieeexplore.ieee.org
In this paper, we study joint beamforming and resource allocation in downlink multi-cell
orthogonal frequency division multiple access (OFDMA) systems. We design a multi-agent …
orthogonal frequency division multiple access (OFDMA) systems. We design a multi-agent …
Deep transfer reinforcement learning for beamforming and resource allocation in multi-cell MISO-OFDMA systems
X Wang, G Sun, Y Xin, T Liu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Orthogonal frequency division multiple access (OFDMA) is one of the promising
technologies to satisfy the huge access demand and high data-rate requirement of the fifth …
technologies to satisfy the huge access demand and high data-rate requirement of the fifth …
Local observations-based energy-efficient multi-cell beamforming via multi-agent reinforcement learning
With affordable overhead on information exchange, energy-efficient beamforming has
potential to achieve both low power consumption and high spectral efficiency. This paper …
potential to achieve both low power consumption and high spectral efficiency. This paper …
相关搜索
- deep reinforcement learning
- multi-agent reinforcement learning
- deep reinforcement heterogeneous networks
- uplink beamforming reinforcement learning
- wireless networks reinforcement learning
- deep reinforcement user association
- deep reinforcement resource allocation
- resource allocation heterogeneous networks
- user association heterogeneous networks
- downlink beamforming power constraints
- downlink beamforming experimental demonstration
- multi-cell beamforming
- transfer reinforcement miso ofdma
- edge update cooperative beamforming
- deep reinforcement downlink beamforming
- downlink beamforming heterogeneous networks