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Video loss prediction model in wireless networks
This work discusses video communications over wireless networks (IEEE 802.11ac standard). The videos are in three different resolutions: 720p, 1080p, and 2160p. It is essential to study the performance of these media in access technologies to enhance the current coding and communications techniques....
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402757/ https://www.ncbi.nlm.nih.gov/pubmed/30840649 http://dx.doi.org/10.1371/journal.pone.0212407 |
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author | Carmona, João Victor Costa Carvalho de Matos, Edemir Marcus Castro, Bruno Souza Lyra Barros, Fabrício José Brito Neto, Miércio Cardoso de Alcântara Pelaes, Evaldo Gonçalves |
author_facet | Carmona, João Victor Costa Carvalho de Matos, Edemir Marcus Castro, Bruno Souza Lyra Barros, Fabrício José Brito Neto, Miércio Cardoso de Alcântara Pelaes, Evaldo Gonçalves |
author_sort | Carmona, João Victor Costa |
collection | PubMed |
description | This work discusses video communications over wireless networks (IEEE 802.11ac standard). The videos are in three different resolutions: 720p, 1080p, and 2160p. It is essential to study the performance of these media in access technologies to enhance the current coding and communications techniques. This study sets out a video quality prediction model that includes the different resolutions that are based on wireless network terms and conditions, an approach that has not previously been adopted in the literature. The model involves obtaining Service and Experience Quality Metrics, such as PSNR (Peak Signal-to-Noise Ratio) and packet loss. This article outlines a methodology and mathematical model for video quality loss in the wireless network from simulated data and its accuracy is ensured through the use of performance metrics (RMSE and Standard Deviation). The methodology is based on two mathematical functions, (logarithmic and exponential), and their parameters are defined by linear regression. The model obtained RMSE values and standard deviation of 2.32 dB and 2.2 dB for the predicted values, respectively. The results should lead to a CODEC (Coder-Decoder) improvement and contribute to a better wireless networks design. |
format | Online Article Text |
id | pubmed-6402757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-64027572019-03-17 Video loss prediction model in wireless networks Carmona, João Victor Costa Carvalho de Matos, Edemir Marcus Castro, Bruno Souza Lyra Barros, Fabrício José Brito Neto, Miércio Cardoso de Alcântara Pelaes, Evaldo Gonçalves PLoS One Research Article This work discusses video communications over wireless networks (IEEE 802.11ac standard). The videos are in three different resolutions: 720p, 1080p, and 2160p. It is essential to study the performance of these media in access technologies to enhance the current coding and communications techniques. This study sets out a video quality prediction model that includes the different resolutions that are based on wireless network terms and conditions, an approach that has not previously been adopted in the literature. The model involves obtaining Service and Experience Quality Metrics, such as PSNR (Peak Signal-to-Noise Ratio) and packet loss. This article outlines a methodology and mathematical model for video quality loss in the wireless network from simulated data and its accuracy is ensured through the use of performance metrics (RMSE and Standard Deviation). The methodology is based on two mathematical functions, (logarithmic and exponential), and their parameters are defined by linear regression. The model obtained RMSE values and standard deviation of 2.32 dB and 2.2 dB for the predicted values, respectively. The results should lead to a CODEC (Coder-Decoder) improvement and contribute to a better wireless networks design. Public Library of Science 2019-03-06 /pmc/articles/PMC6402757/ /pubmed/30840649 http://dx.doi.org/10.1371/journal.pone.0212407 Text en © 2019 Carmona et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Carmona, João Victor Costa Carvalho de Matos, Edemir Marcus Castro, Bruno Souza Lyra Barros, Fabrício José Brito Neto, Miércio Cardoso de Alcântara Pelaes, Evaldo Gonçalves Video loss prediction model in wireless networks |
title | Video loss prediction model in wireless networks |
title_full | Video loss prediction model in wireless networks |
title_fullStr | Video loss prediction model in wireless networks |
title_full_unstemmed | Video loss prediction model in wireless networks |
title_short | Video loss prediction model in wireless networks |
title_sort | video loss prediction model in wireless networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402757/ https://www.ncbi.nlm.nih.gov/pubmed/30840649 http://dx.doi.org/10.1371/journal.pone.0212407 |
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