FMO selection using Markov model in H.264 for slow fading wireless channels
In this paper, we present a framework on how to more effectively utilize FMO for video transmission with low bandwidth and low delay constraints under slow fading wireless channel impairments using markov model for channel prediction. The condition of the channel is predicted to be good or bad based...
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description | In this paper, we present a framework on how to more effectively utilize FMO for video transmission with low bandwidth and low delay constraints under slow fading wireless channel impairments using markov model for channel prediction. The condition of the channel is predicted to be good or bad based on the feedback information from the decoder. FMO is enabled with different number of slice groups during the times that the channel is predicted to be experiencing burst errors. This scheme fully utilizes the error resilient properties of FMO by disabling FMO during the times that the channel is good. For the transmission systems under test at 20 kbps, the proposed scheme of adaptive FMO mode selection can obtain a 0.5 dB improvement in PSNR as compared to other schemes with FMO enabled for the entire video sequence. |
doi_str_mv | 10.1109/ISCIT.2010.5665157 |
format | Conference Proceeding |
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For the transmission systems under test at 20 kbps, the proposed scheme of adaptive FMO mode selection can obtain a 0.5 dB improvement in PSNR as compared to other schemes with FMO enabled for the entire video sequence.</description><subject>Automatic voltage control</subject><subject>Computational modeling</subject><subject>Encoding</subject><subject>Fading</subject><subject>Markov processes</subject><subject>Predictive models</subject><subject>Wireless communication</subject><isbn>1424470072</isbn><isbn>9781424470075</isbn><isbn>9781424470099</isbn><isbn>9781424470105</isbn><isbn>1424470099</isbn><isbn>1424470102</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1T81OwzAYC0JIwOgLwCUv0PLlvzmiirGKTTvQ-_QtTSDQtagZTLz9ihi-WLZsSybklkHBGNj7-qWqm4LDpJXWiilzRjJrSia5lAbA2nNy_S8MvyRZSu8wQXEjJLsiz_PVmibfebePQ0-_Uuxf6QrHj-Gb7obWdzT2dFFwLWkYRpq64UADtr-pQxynXkrUvWHf-y7dkIuAXfLZiWekmT821SJfrp_q6mGZRwv7XMvgwlYygBLLslUOlbDWKrO16DVDpYVjXnHdonIGfDsZAQwIZIoxLMWM3P3NRu_95nOMOxx_Nqf74giknEzL</recordid><startdate>201010</startdate><enddate>201010</enddate><creator>Cajote, R D</creator><creator>Aramvith, S</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201010</creationdate><title>FMO selection using Markov model in H.264 for slow fading wireless channels</title><author>Cajote, R D ; Aramvith, S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-64fcfb41008a88d5ca5399957b9ae61a563c1e526da5c70ed563f0703a1511a83</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Automatic voltage control</topic><topic>Computational modeling</topic><topic>Encoding</topic><topic>Fading</topic><topic>Markov processes</topic><topic>Predictive models</topic><topic>Wireless communication</topic><toplevel>online_resources</toplevel><creatorcontrib>Cajote, R D</creatorcontrib><creatorcontrib>Aramvith, S</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Cajote, R D</au><au>Aramvith, S</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>FMO selection using Markov model in H.264 for slow fading wireless channels</atitle><btitle>2010 10th International Symposium on Communications and Information Technologies</btitle><stitle>ISCIT</stitle><date>2010-10</date><risdate>2010</risdate><spage>1131</spage><epage>1135</epage><pages>1131-1135</pages><isbn>1424470072</isbn><isbn>9781424470075</isbn><eisbn>9781424470099</eisbn><eisbn>9781424470105</eisbn><eisbn>1424470099</eisbn><eisbn>1424470102</eisbn><abstract>In this paper, we present a framework on how to more effectively utilize FMO for video transmission with low bandwidth and low delay constraints under slow fading wireless channel impairments using markov model for channel prediction. The condition of the channel is predicted to be good or bad based on the feedback information from the decoder. FMO is enabled with different number of slice groups during the times that the channel is predicted to be experiencing burst errors. This scheme fully utilizes the error resilient properties of FMO by disabling FMO during the times that the channel is good. For the transmission systems under test at 20 kbps, the proposed scheme of adaptive FMO mode selection can obtain a 0.5 dB improvement in PSNR as compared to other schemes with FMO enabled for the entire video sequence.</abstract><pub>IEEE</pub><doi>10.1109/ISCIT.2010.5665157</doi><tpages>5</tpages></addata></record> |
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subjects | Automatic voltage control Computational modeling Encoding Fading Markov processes Predictive models Wireless communication |
title | FMO selection using Markov model in H.264 for slow fading wireless channels |
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