WGAN-Based Oversampling for QoS-Aware M2M Network Power Allocation

J Zhou, Y Tao - 2024 International Conference on Computing …, 2024 - ieeexplore.ieee.org
Internet of Things (IoT) in the new era of 5G and 6G. Pursuing an autonomous strategy for
optimal power allocation remains a significant research topic in M2M communication …

Xcelerate5G: Optimizing Resource Allocation Strategies for 5G Network Using ML

N Shukla, A Siloiya, A Singh… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
As we embrace the transformative era of 5G technology, promising unprecedented data
rates, minimal latency, and extensive device connectivity, the need for effective resource …

[PDF][PDF] A Deep Reinforcement Learning-Based Technique for Optimal Power Allocation in Multiple Access Communications.

S Soltani, E Ghafourian, R Salehi… - … Automation & Soft …, 2024 - cdn.techscience.cn
For many years, researchers have explored power allocation (PA) algorithms driven by
models in wireless networks where multiple-user communications with interference are …

WIP: Demand-driven power allocation in wireless networks with deep Q-learning

A Giannopoulos, S Spantideas… - 2021 IEEE 22nd …, 2021 - ieeexplore.ieee.org
Power allocation is strongly related to the coverage and capacity of wireless networks,
playing a critical role in the development of 5G networks. This paper proposes a Demand …

Power allocation in multi-user cellular networks with deep Q learning approach

F Meng, P Chen, L Wu - ICC 2019-2019 IEEE International …, 2019 - ieeexplore.ieee.org
The model-driven power allocation (PA) algorithms in the wireless cellular networks with
interfering multiple-access channel (IMAC) have been investigated for decades. Nowadays …

MultiNet: Deep unsupervised power control for industrial MU-MIMO networks

R Maiti, AS Madhukumar, TZH Ernest - Physical Communication, 2023 - Elsevier
This paper presents Multinet, an unsupervised deep learning (DL) approach for power
allocation in industrial environments and IIoT applications. Multinet extends the previously …

Energy-Efficient Uplink Power Allocation in Ultra-Dense Network Through Multi-agent Reinforcement Learning

Y Zhao, T Peng, Y Guo, W Wang - 2021 IEEE 94th Vehicular …, 2021 - ieeexplore.ieee.org
Energy efficiency (EE) is acknowledged as a key performance indicator for 5G networks.
This paper mainly studies the problem of energy efficient power allocation in 5G Ultra-dense …

Machine intelligence at the edge with learning centric power allocation

S Wang, YC Wu, M Xia, R Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
While machine-type communication (MTC) devices generate considerable amounts of data,
they often cannot process the data due to limited energy and computational power. To …

Learning centric power allocation for edge intelligence

S Wang, R Wang, Q Hao, YC Wu… - ICC 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
While machine-type communication (MTC) devices generate massive data, they often
cannot process this data due to limited energy and computation power. To this end, edge …

Learning-based joint power and channel assignment for hyper dense 5G networks

AH Arani, A Mehbodniya, MJ Omidi… - 2016 IEEE International …, 2016 - ieeexplore.ieee.org
Next generation mobile networks will face the unprecedented demand for higher data rates.
To satisfy this demand, the dense deployment of heterogeneous wireless networks …