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

2021 ◽  
Author(s):  
Glaucio Ramos ◽  
Carlos Vargas ◽  
Luiz Mello ◽  
Paulo Pereira ◽  
Robson Vieira ◽  
...  
Keyword(s):  
Short Range ◽  
Prediction Models ◽  
Path Loss ◽  
Prediction Method ◽  
Additional Parameter ◽  
University Campus ◽  
Millimetre Wave ◽  
Loss Prediction ◽  
Path Loss Prediction ◽  
The Difference

Abstract In this paper, we present the results of short-range path loss measurement 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 difference between transmitter and receiver is proposed. The main contribution of this paper is the use of the Fuzzy technique to perform path loss predictions for short links in the millimetre wave range, from 27 to 40 GHz, providing lower errors when compared to the traditional ABG and CIF models. However, it should be noted that the Fuzzy technique uses a set of equations to perform the prediction and the attenuation coefficient is not explicit as in the classical models. Also, a non-negligible correlation between the difference in height between transmitter and receiver positions and the path loss in such short links (i.e., the path inclination) has been observed and requires further investigation. If confirmed, it could provide an additional parameter to improve the accuracy of the traditional ABG model.

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.

1.25 GHz path loss prediction models for multifloored buildings

2009 ◽  
Author(s):  
Ismail Fauzi Isnin ◽  
Martin Tomlinson ◽  
Mohammed Zaki Ahmed ◽  
Marcel Ambroze
Keyword(s):  
Prediction Models ◽  
Path Loss ◽  
Loss Prediction ◽  
Path Loss Prediction

scholarly journals Slope-based Empirical Path Loss Prediction Models for rural networks at 2.4 GHz

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Jean Louis Ebongue Kedieng Fendji . ◽  
Nelson Maguelva Mafai . ◽  
Jean Michel Nlong .
Keyword(s):  
Prediction Models ◽  
Path Loss ◽  
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 A New SVM-Based Modeling Method of Cabin Path Loss Prediction

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Xiaonan Zhao ◽  
Chunping Hou ◽  
Qing Wang
Keyword(s):  
Support Vector Machine ◽  
Path Loss ◽  
Prediction Method ◽  
Modeling Method ◽  
Support Vector ◽  
Propagation Modeling ◽  
Fitting Method ◽  
Loss Prediction ◽  
Path Loss Prediction ◽  
Curve Fitting Method

A new modeling method of cabin path loss prediction based on support vector machine (SVM) is proposed in this paper. The method is trained with the path loss values of measured points inside the cabin and can be used to predict the path loss values of the unmeasured points. The experimental results demonstrate that our modeling method is more accurate than the curve fitting method. This SVM-based path loss prediction method makes the prediction much easier and more accurate, which covers performance traditional methods in the channel propagation modeling.

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