Joint Random Forest and Particle Swarm Optimization for Predictive Pathloss Modeling of Wireless Signals from Cellular Networks

Joint Random Forest and Particle Swarm Optimization for Predictive Pathloss Modeling of Wireless Signals from Cellular Networks

The accurate and reliable predictive estimation of signal attenuation loss is of prime importance in radio resource management. During wireless network design and planning, a reliable path loss model is required for optimal predictive estimation of the received signal strength, coverage, quality, an...

Full description

Bibliographic Details
Main Authors: Okiemute Roberts Omasheye, Samuel Azi, Joseph Isabona, Agbotiname Lucky Imoize, Chun-Ta Li, Cheng-Chi Lee
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Future Internet
Subjects:
path loss measurement
signal strength intensity
particle swarm optimization
random forest
hybrid RF-PS model
wireless network modeling
Online Access:https://www.mdpi.com/1999-5903/14/12/373

Similar Items

Similar Items