Delay root cause analysis and 3D modeling of LTE control communication using machine learning
[ X ]
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Altınbaş Üniversitesi / Lisansüstü Eğitim Enstitüsü
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This thesis examines delay root cause analysis and 3D modeling of LTE control
communication utilizing sophisticated machine learning for network testing. The research
studied LTE protocols for 5th-generation mobile telephony and provided guidelines for
controlling LTE frequency for background knowledge, although this work has an independent
technique that does not employ LTE standards. Input-output MIMO with 512 elements for
100-GHz and 128 elements for mid-band sub-6-GHz has been used. LOS is always 0.5. This
paper is about LTE, not 3D modeling of LTE control path loss type communication using
machine learning. This work's route loss depends on cross-pol beam LTE polarization (±45o).
Rx and Tx activities at 0.5 km and 15.25 m altitude. Distance, handover authentication, rain,
atmosphere, and sub-6GHz vs 100GHz weather conditions effect pathloss. Enhancing
transmission power and efficiency improved spatial variety. Authorizing and sanctioning
ANN-based LTE frequency for both mid-band sub-6-GHz and 100-GHz is possible due to its
planning and development using open-source material and strategy with high transmission
power and rate under questionable handover confirmation using MIMO input/yield receiving
wires. This theory examines LTE innovation dimensioning as unbiased for various handover
verification and allows input boundary alterations for various organization arrangement setups for LTE recurrent data transmission from 6 GHz to 100 GHz for three climate sorts. This cycle
should be seen as an undeniable level way to examine LTE networks under various air
conditions. Using signal handling tool compartment and explicit AI-based ANN calculation
from AI toolkit in MATLAB R2019a, it is possible to create a result answer for three climate
types in dataset with an LTE communication level of exactness of downpour assimilation and
abundance foliage mis fort.
Açıklama
Anahtar Kelimeler
LTE, Investigation, MIMO, Artificial Neural Network, Antennas
Kaynak
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Mohammed, Sameer Qutaiba. (2022). Delay root cause analysis and 3D modeling of LTE control communication using machine learning. (Yayınlanmamış yüksek lisans tezi). Altınbaş Üniversitesi, Lisansüstü Eğitim Enstitüsü, İstanbul.
