scholarly journals Improved Propagation Models for LTE Path Loss Prediction in Urban & Suburban Ghana

2019 ◽  
Vol 11 (6) ◽  
pp. 35-53
Author(s):  
James D Gadze ◽  
Kwame A Agyekum ◽  
Stephen J Nuagah ◽  
E.A. Affum
Keyword(s):  
Path Loss ◽  
Propagation Models ◽  
Loss Prediction ◽  
Path Loss Prediction

scholarly journals Modeling the Distribution of Radiofrequency Intensities from the Digital Terrestrial Television (DTTV) Broadcasting Transmitter in Kampala Metropolitan; Uganda

2020 ◽  
pp. 65-78
Author(s):  
Peter Opio ◽  
Akisophel Kisolo ◽  
Tumps W. Ireeta ◽  
Willy Okullo
Keyword(s):  
Prediction Models ◽  
Reference Signal ◽  
Path Loss ◽  
Analysis Software ◽  
Propagation Models ◽  
Received Power ◽  
Loss Prediction ◽  
Path Loss Prediction ◽  
Digital Terrestrial Television ◽  
The One

This study presents the modeling of the distribution of RF intensities from the Digital Terrestrial Television (DTTV) broadcasting transmitter in Kampala metropolitan. To  achieve this, the performance evaluation of the different path loss propagation models and envisaging the one most suitable for Kampala metropolitan was done by comparing the path loss model values with the measured field Reference Signal Received  Power (RSRP) values. The RSRP of the DTTV broadcasting transmitter were measured at operating frequencies of 526 MHz, 638 MHz, 730 MHz and 766 MHz using the Aaronia  Spectran HF-6065 V4 spectrum analyzer, Aaronia AG HyperLOG 4025 Antenna at 1.5 m and 2.5 m heights, Aaronia GPS Logger, real time Aaronia MCS spectrum-analysis-software and   a T430s Lenovo Laptop. On comparing the measured path loss values with the various  path loss prediction model values, results showed that Egli and Davidson models are the  most accurate and reliable path loss prediction models for the distribution of DTTV RF  intensities in Kampala metropolitan, since their Root Mean Square Error values were the least for both routes.

scholarly journals ANFIS Model for Path Loss Prediction in the GSM and WCDMA Bands in Urban Area

2019 ◽  
Vol 18 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Nasir Faruk ◽  
N. T. Surajudeen-Bakinde ◽  
Abubakar Abdulkarim ◽  
Segun I. Popoola ◽  
A. Abdulkarim ◽  
...  
Keyword(s):  
Urban Areas ◽  
Communication Systems ◽  
Research Work ◽  
Path Loss ◽  
Theoretical Models ◽  
Anfis Model ◽  
Propagation Models ◽  
Reliable Model ◽  
Loss Prediction ◽  
Path Loss Prediction

Path loss propagation is a vital concern when designing and planning networks in mobile communication systems. Propagation models such as the empirical, deterministic and theoretical models, which possess complex, inconsistent, time-consuming and non-adaptable features, have proven to be inefficient in designing of wireless systems, thereby resulting in the need for a more reliable model. Artificial Intelligence methods seem to overcome the drawbacks of the propagation models for predicting path loss. In this paper, the ANFIS approach to path loss prediction in the GSM and WCDMA bands is presented for selected urban areas in Nigeria. Furthermore, the effects of the number of Membership Functions (MFs) are investigated. The prediction results indicated that the ANFIS model outperformed the Hata, Cost-231, Egli and ECC-33 models in both Kano and Abuja urban areas. In addition, an increase in the number of MFs conceded an improved RMSE result for the generalized bell-shaped MF. The general performance and outcome of this research work show the efficiency and usefulness of the ANFIS model in improving prediction accuracy over propagation models

scholarly journals Fusing Diverse Input Modalities for Path Loss Prediction: A Deep Learning Approach

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 30441-30451
Author(s):  
Sotirios P. Sotiroudis ◽  
Panagiotis Sarigiannidis ◽  
Sotirios K. Goudos ◽  
Katherine Siakavara
Keyword(s):  
Deep Learning ◽  
Path Loss ◽  
Learning Approach ◽  
Loss Prediction ◽  
Path Loss Prediction

Calibration of Empirical Models for Path Loss Prediction in Urban Environment

2020 ◽  
pp. 301-310
Author(s):  
Robert O. Abolade ◽  
Dare J. Akintade ◽  
Segun I. Popoola ◽  
Folasade A. Semire ◽  
Aderemi A. Atayero ◽  
...  
Keyword(s):  
Urban Environment ◽  
Path Loss ◽  
Empirical Models ◽  
Loss Prediction ◽  
Path Loss Prediction

scholarly journals Path loss prediction model development in a mountainous forest environment

2021 ◽  
pp. 1-1
Author(s):  
Bilguunmaa Myagmardulam ◽  
Tadachika Nakayama ◽  
Kazuyoshi Takahashi ◽  
Ryu Miura ◽  
Fumie Ono ◽  
...  
Keyword(s):  
Prediction Model ◽  
Model Development ◽  
Path Loss ◽  
Forest Environment ◽  
Loss Prediction ◽  
Path Loss Prediction

scholarly journals Measurement and Prediction of Short-Range Path Loss between 27 and 40 GHz in University Campus Scenarios

2020 ◽  
Author(s):  
Glaucio Ramos ◽  
Carlos Vargas ◽  
Luiz Mello ◽  
Paulo Pereira ◽  
Sandro Gonçalves ◽  
...  
Keyword(s):  
Short Range ◽  
Prediction Models ◽  
Path Loss ◽  
Prediction Method ◽  
University Campus ◽  
Millimetre Wave ◽  
Empirical Prediction ◽  
Loss Prediction ◽  
Path Loss Prediction ◽  
Path Loss Measurements

Abstract In this paper, we present the results of short-range path loss measurements in the microwave and millimetre wave bands, at frequencies between 27 and 40 GHz, obtained in a campaign inside a university campus in Rio de Janeiro, Brazil. Existing empirical path loss prediction models, including the alpha-beta-gamma (ABG) model and the close-in free space reference distance with frequency dependent path loss exponent (CIF) model are tested against the measured data, and an improved prediction method that includes the path loss dependence on the height di erence between transmitter and receiver is proposed. A fuzzy technique is also applied to predict the path loss and the results are compared with those obtained with the empirical prediction models.

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