Model-aided deep learning method for path loss prediction in mobile communication systems at 2.6 GHz

J Thrane, D Zibar, HL Christiansen - Ieee Access, 2020 - ieeexplore.ieee.org
Accurate channel models are essential to evaluate mobile communication system
performance and optimize coverage for existing deployments. The introduction of various …

Performance of path loss models over mid-band and high-band channels for 5G communication networks: A review

FE Shaibu, EN Onwuka, N Salawu, SS Oyewobi… - Future Internet, 2023 - mdpi.com
The rapid development of 5G communication networks has ushered in a new era of high-
speed, low-latency wireless connectivity, as well as the enabling of transformative …

From Simulators to Digital Twins for Enabling Emerging Cellular Networks: A Tutorial and Survey

M Manalastas, MUB Farooq, SMA Zaidi… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Simulators are indispensable parts of the research and development necessary to advance
countless industries, including cellular networks. With simulators, the evaluation, analysis …

Determination of neural network parameters for path loss prediction in very high frequency wireless channel

SI Popoola, A Jefia, AA Atayero, O Kingsley… - IEEE …, 2019 - ieeexplore.ieee.org
It is very important to understand the input features and the neural network parameters
required for optimal path loss prediction in wireless communication channels. In this paper …

Kinetic, thermodynamic and artificial neural network prediction studies on co-pyrolysis of the agricultural waste and algae

Q Wang, R Wang, Z Li, Y Zhao, Q Cao, F Han, Y Gao - Renewable Energy, 2024 - Elsevier
The thermal decomposition behaviors of Maize straw (MS), algae (AL), and their blends
were studied in a thermogravimetric analyzer to evaluate the bio-energy potential in this …

Path loss predictions in the VHF and UHF bands within urban environments: Experimental investigation of empirical, heuristics and geospatial models

N Faruk, SI Popoola, NT Surajudeen-Bakinde… - IEEE …, 2019 - ieeexplore.ieee.org
Deep knowledge of how radio waves behave in a practical wireless channel is required for
effective planning and deployment of radio access networks in urban environments …

Cellular network radio propagation modeling with deep convolutional neural networks

X Zhang, X Shu, B Zhang, J Ren, L Zhou… - Proceedings of the 26th …, 2020 - dl.acm.org
Radio propagation modeling and prediction is fundamental for modern cellular network
planning and optimization. Conventional radio propagation models fall into two categories …

CNN-based mmWave path loss modeling for fixed wireless access in suburban scenarios

H Cheng, S Ma, H Lee - IEEE antennas and wireless …, 2020 - ieeexplore.ieee.org
Path loss modeling of millimeter waves is regarded as one of the most challenging problems
in the design of the fifth-generation (5G) mobile communication networks due to the high …

Comparative analysis of major machine-learning-based path loss models for enclosed indoor channels

MK Elmezughi, O Salih, TJ Afullo, KJ Duffy - Sensors, 2022 - mdpi.com
Unlimited access to information and data sharing wherever and at any time for anyone and
anything is a fundamental component of fifth-generation (5G) wireless communication and …

Millimeter wave path loss modeling for 5G communications using deep learning with dilated convolution and attention

H Cheng, S Ma, H Lee, M Cho - IEEE Access, 2021 - ieeexplore.ieee.org
An accurate and efficient path loss modeling method for millimeter wave communications
plays a significant role in the large-scale deployment of a fifth-generation (5G) mobile …