Dynamic power allocation in IIoT based on multi-agent deep reinforcement learning
F Li, Z Liu, X Zhang, Y Yang - Neurocomputing, 2022 - Elsevier
With the rapidly growing fifth generation (5G) wireless data traffic, the cellular network has
gradually become an important mode for the Industrial Internet of Things (IIoT). To give full …
gradually become an important mode for the Industrial Internet of Things (IIoT). To give full …
Dynamic power allocation in cellular network based on multi-agent double deep reinforcement learning
Y Yang, F Li, X Zhang, Z Liu, KY Chan - Computer Networks, 2022 - Elsevier
With the massively growing wireless data traffic, the dense cellular network has become a
significant mode for the fifth generation (5G) network. To fully utilize the benefit of the cellular …
significant mode for the fifth generation (5G) network. To fully utilize the benefit of the cellular …
Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks
This work demonstrates the potential of deep reinforcement learning techniques for transmit
power control in wireless networks. Existing techniques typically find near-optimal power …
power control in wireless networks. Existing techniques typically find near-optimal power …
Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks
Y Sinan Nasir, D Guo - arXiv e-prints, 2018 - ui.adsabs.harvard.edu
This work demonstrates the potential of deep reinforcement learning techniques for transmit
power control in wireless networks. Existing techniques typically find near-optimal power …
power control in wireless networks. Existing techniques typically find near-optimal power …
Joint ddpg and unsupervised learning for channel allocation and power control in centralized wireless cellular networks
M Sun, E Mei, S Wang, Y Jin - Ieee Access, 2023 - ieeexplore.ieee.org
In order to solve the resource allocation problem in scenarios of centralized wireless cellular
communication with multiple cells, users and channels, a novel resource allocation …
communication with multiple cells, users and channels, a novel resource allocation …
A deep Q-learning method for downlink power allocation in multi-cell networks
Optimal resource allocation is a fundamental challenge for dense and heterogeneous
wireless networks with massive wireless connections. Because of the non-convex nature of …
wireless networks with massive wireless connections. Because of the non-convex nature of …
Federated learning for distributed energy-efficient resource allocation
In cellular networks, resource allocation is performed in a centralized way, which brings
huge computation complexity to the base station (BS) and high transmission overhead. This …
huge computation complexity to the base station (BS) and high transmission overhead. This …
MADRL Based Uplink Joint Resource Block Allocation and Power Control in Multi-Cell Systems
Intelligent resource allocation and power control schemes are regarded as important
methods to alleviate the problems caused by the sharp increase in the number of users and …
methods to alleviate the problems caused by the sharp increase in the number of users and …
Power allocation in multi-user cellular networks: Deep reinforcement learning approaches
The model-based power allocation has been investigated for decades, but this approach
requires mathematical models to be analytically tractable and it has high computational …
requires mathematical models to be analytically tractable and it has high computational …
A deep reinforcement learning for user association and power control in heterogeneous networks
Heterogeneous network (HetNet) is a promising solution to satisfy the unprecedented
demand for higher data rate in the next generation mobile networks. Different from the …
demand for higher data rate in the next generation mobile networks. Different from the …