Machine Learning Approaches for Radio Propagation Modeling in Urban Vehicular Channels
The use of vehicular communications is anticipated to improve safety in road traffic. The traditional radio channel models that describe the effects of radio wave propagation in dynamic vehicular environments have their own limitations. In this paper, machine learning (ML) techniques are applied for...
Main Authors: | Khalil Ahmad, Sajjad Hussain |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9933738/ |
Similar Items
-
Deterministic 3D Ray-Launching Millimeter Wave Channel Characterization for Vehicular Communications in Urban Environments
by: Fidel Alejandro Rodríguez-Corbo, et al.
Published: (2020-09-01) -
MLP and CNN-based Classification of Points of Interest in Side-channel Attacks
by: Hanwen Feng, et al.
Published: (2020-04-01) -
Propagation Models in Vehicular Communications
by: Fidel Alejandro Rodriguez-Corbo, et al.
Published: (2021-01-01) -
Utilizing Different Machine Learning Techniques to Examine Speeding Violations
by: Ahmad H. Alomari, et al.
Published: (2023-04-01) -
Improving Spatial Agreement in Machine Learning-Based Landslide Susceptibility Mapping
by: Mohammed Sarfaraz Gani Adnan, et al.
Published: (2020-10-01)