Comparative Analysis of Machine Learning Algorithms for 5G Coverage Prediction: Identification of Dominant Feature Parameters and Prediction Accuracy
H Yuliana - IEEE Access, 2024 - ieeexplore.ieee.org
5G technology is a key factor in delivering faster and more reliable wireless connectivity.
One crucial aspect in 5G network planning is coverage prediction, which enables network …
One crucial aspect in 5G network planning is coverage prediction, which enables network …
Improvement of Deep Learning-Based Reference Signal Received Power Prediction for LTE Communication System
D Chomsuay, W Phakphisut… - … on Circuits/Systems …, 2023 - ieeexplore.ieee.org
Recently, in our previous work [3], we have proposed the deep learning-based reference
signal received power (RSRP) prediction for LTE communication system. However, in this …
signal received power (RSRP) prediction for LTE communication system. However, in this …
Reference Signal Received Power Prediction Using Convolutional Neural Network with Residual Loss
T Ngenjaroendee, W Phakphisut… - … on Circuits/Systems …, 2023 - ieeexplore.ieee.org
In this paper, LTE measurement reports collected from user equipments are used to
generate the residual loss, which can represent the loss value of each grid. The residual …
generate the residual loss, which can represent the loss value of each grid. The residual …