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Path Loss Correction for Signal Propagation amongst Low Roof Top Buildings using Fuzzy Logic

by Sumit Joshi, Govind Sati, Mukesh Chandra Kestwal
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 83 - Number 17
Year of Publication: 2013
Authors: Sumit Joshi, Govind Sati, Mukesh Chandra Kestwal
10.5120/14673-2744

Sumit Joshi, Govind Sati, Mukesh Chandra Kestwal . Path Loss Correction for Signal Propagation amongst Low Roof Top Buildings using Fuzzy Logic. International Journal of Computer Applications. 83, 17 ( December 2013), 43-48. DOI=10.5120/14673-2744

@article{ 10.5120/14673-2744,
author = { Sumit Joshi, Govind Sati, Mukesh Chandra Kestwal },
title = { Path Loss Correction for Signal Propagation amongst Low Roof Top Buildings using Fuzzy Logic },
journal = { International Journal of Computer Applications },
issue_date = { December 2013 },
volume = { 83 },
number = { 17 },
month = { December },
year = { 2013 },
issn = { 0975-8887 },
pages = { 43-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume83/number17/14673-2744/ },
doi = { 10.5120/14673-2744 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:59:41.987975+05:30
%A Sumit Joshi
%A Govind Sati
%A Mukesh Chandra Kestwal
%T Path Loss Correction for Signal Propagation amongst Low Roof Top Buildings using Fuzzy Logic
%J International Journal of Computer Applications
%@ 0975-8887
%V 83
%N 17
%P 43-48
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Performance of current path attenuation prediction models encounters huge deviation from their true behavior when deployed for the locality apart from the one for which it had been proven for. This work deals with introducing the path loss on the basis of measured data and representation of the same in a different approach for the mentioned Fuzzy Inference system based analysis. The empirical data collection followed by curve-fitting for path loss evaluation on decibel scale with Normal random variable distribution for representing the shadow fading. Our paper introduces a new methodology for prediction of path loss for betterment in QoS via. Network planning specifically for mobility prone communication systems deploying fuzzy approach. The Transmission discontinuities encountered during propagation has been differentiated in to a variety of factors defined as fuzzy sets such as free space, flat terrain, low foliage terrain, high foliage terrain, and country side terrain. path loss exponent (n) has been applied for varied propagation profiles, Mamdani Fuzzy Inference has been deployed for prediction of "n" path loss exponent for any kind of scenario, which was obtained on the basis of set of symbolic rules that avails an approximation to the known propagation scenarios. Bertoni's model proposed by H. L. Bertoni's has been used for the present analysis.

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Index Terms

Computer Science
Information Sciences

Keywords

Path loss measurement Path loss predication Fuzzy Inference Fuzzy Modeling.

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