This study discusses biochar and machine learning application. Concept of biochar, machine learning and different machine learning algorithms used for predicting adsorption …
J Guo, C Yang - IEEE Transactions on Wireless …, 2021 - ieeexplore.ieee.org
A well-trained deep neural network (DNN) enables real-time resource allocation by learning the relationship between a policy and its impacting parameters. When wireless systems …
Unmanned aerial vehicle (UAV) assisted wireless communication has recently been recognized as an inevitably promising component of future wireless networks. Particularly …
H Huang, M Liu, G Gui, H Gacanin… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Energy-efficiency (EE) is a critical metric within wireless optimization. Power control over fading channels is considered as a promising EE-improving technique, but requires …
Current maritime communications mainly rely on satellites having meager transmission resources, hence suffering from poorer performance than modern terrestrial wireless …
This study analyses the main challenges, trends, technological approaches, and artificial intelligence methods developed by new researchers and professionals in the field of …
H Huang, Y Lin, G Gui, H Gacanin… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Unsupervised learning (UL) is widely used in the wireless resource allocation problems due to its lower computational complexity and better performance compared with traditional …
In the sixth-generation (6G) networks, newly emerging diversified services of massive users in dynamic network environments are required to be satisfied by multi-dimensional …
D Yu, H Lee, SH Park, SE Hong - IEEE Wireless …, 2021 - ieeexplore.ieee.org
Cooperative beamforming across access points (APs) and fronthaul quantization strategies are essential for cloud radio access network (C-RAN) systems. The nonconvexity of the C …