Machine learning for radio propagation modeling: a comprehensive survey
M Vasudevan, M Yuksel - IEEE Open Journal of the …, 2024 - ieeexplore.ieee.org
With recent advancements in the telecommunication industry and the deployment of 5G
networks, radio propagation modeling is considered a fundamental task in planning and …
networks, radio propagation modeling is considered a fundamental task in planning and …
Generative AI Empowered Network Digital Twins: Architecture, Technologies, and Applications
The rapid advancement of mobile networks highlights the limitations of traditional network
planning and optimization methods, particularly in modeling, evaluation, and application …
planning and optimization methods, particularly in modeling, evaluation, and application …
Channel path loss prediction using satellite images: A deep learning approach
With the advancement of communication technology, there is a higher demand for high-
precision and high-generalization channel path loss models as it is fundamental to …
precision and high-generalization channel path loss models as it is fundamental to …
PMNet: Robust pathloss map prediction via supervised learning
Pathloss prediction is an essential component of wireless network planning. While ray
tracing based methods have been successfully used for many years, they require significant …
tracing based methods have been successfully used for many years, they require significant …
Overview of the First Pathloss Radio Map Prediction Challenge
Pathloss quantifies the reduction in power density of a signal radiated from a transmitter. The
attenuation is due to large-scale effects such as free-space propagation loss and …
attenuation is due to large-scale effects such as free-space propagation loss and …
Channel estimation via loss field: Accurate site-trained modeling for shadowing prediction
J Wang, MG Weldegebriel… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Future networks which share spectrum dynamically among groups of mobile users will
require fast and accurate channel estimation in order to guarantee signal-to-interference …
require fast and accurate channel estimation in order to guarantee signal-to-interference …
Sparse Channel Reconstruction: A Generative Adversarial Network-Based Approach
Wireless channels typically exhibit a sparse structure, with sparsity regarded as an inherent
characteristics. A deeper understanding and accurate representation of channel sparsity …
characteristics. A deeper understanding and accurate representation of channel sparsity …
Augmenting channel estimation via loss field: Site-trained Bayesian modeling and comparative analysis
Future wireless networks that share spectrum dynamically among groups of mobile users
will require fast and accurate channel estimation in order to guarantee varying signal-to …
will require fast and accurate channel estimation in order to guarantee varying signal-to …
How generative models improve LOS estimation in 6G non-terrestrial networks
With the advent of 5G and the anticipated arrival of 6G, there has been a growing research
interest in combining mobile networks with Non-Terrestrial Network platforms such as low …
interest in combining mobile networks with Non-Terrestrial Network platforms such as low …
Online Radio Environment Map Creation via UAV Vision for Aerial Networks
NC Matson, K Sundaresan - IEEE INFOCOM 2024-IEEE …, 2024 - ieeexplore.ieee.org
Radio environment maps provide a comprehensive spatial view of the wireless channel and
are especially useful in on-demand UAV wireless networks where operators are not afforded …
are especially useful in on-demand UAV wireless networks where operators are not afforded …