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Reseach Article

Best Fit Wavelet Function for Path Loss Prediction in Wireless Communication System

by Kishor K. Pandyaji, S.K. Bodhe
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 135 - Number 12
Year of Publication: 2016
Authors: Kishor K. Pandyaji, S.K. Bodhe
10.5120/ijca2016908585

Kishor K. Pandyaji, S.K. Bodhe . Best Fit Wavelet Function for Path Loss Prediction in Wireless Communication System. International Journal of Computer Applications. 135, 12 ( February 2016), 30-34. DOI=10.5120/ijca2016908585

@article{ 10.5120/ijca2016908585,
author = { Kishor K. Pandyaji, S.K. Bodhe },
title = { Best Fit Wavelet Function for Path Loss Prediction in Wireless Communication System },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 135 },
number = { 12 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 30-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume135/number12/24102-2016908585/ },
doi = { 10.5120/ijca2016908585 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:35:37.602307+05:30
%A Kishor K. Pandyaji
%A S.K. Bodhe
%T Best Fit Wavelet Function for Path Loss Prediction in Wireless Communication System
%J International Journal of Computer Applications
%@ 0975-8887
%V 135
%N 12
%P 30-34
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The site-specific or statistical channel models can be precisely characterize the propagation channel, their parameters depend on channel statistics and accurate database, making them difficult for implementation. In mobile communication system, a simple model with few parameters to estimate or transmit is of great interest. A new model is proposed using both Fourier and Wavelet transform as a decomposition basis for outdoor propagation. The path loss is decomposed on wavelet packet basis function resulting in scaling and wavelet coefficients. Hard thresholding is used to compress these coefficients as much as possible. Different threshold levels have been tested to find the mean square error (MSE) due to reconstructed path loss after compression. Propagation models for mobile communication system have been evaluated and compared based on this modeling scheme.

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Index Terms

Computer Science
Information Sciences

Keywords

Propagation model Path loss Best fit Wavelet function Hard and soft thresholding