{"id":155218,"date":"1999-05-01T00:00:00","date_gmt":"1999-05-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/fec-and-pseudo-arq-for-receiver-driven-layered-multicast\/"},"modified":"2018-10-16T22:02:32","modified_gmt":"2018-10-17T05:02:32","slug":"fec-and-pseudo-arq-for-receiver-driven-layered-multicast","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/fec-and-pseudo-arq-for-receiver-driven-layered-multicast\/","title":{"rendered":"FEC and pseudo-ARQ for receiver-driven layered multicast"},"content":{"rendered":"

We consider the problem of joint source\/channel coding of real-time sources, such as audio and video, for the purpose of multicasting over the Internet. The sender injects into the network multiple source layers and multiple channel (parity) layers, some of which are delayed relative to the source. Each receiver subscribes to the number of source layers and the number of channel layers that optimizes the source-channel rate allocation for that receiver’s available bandwidth and packet loss probability. We augment this layered FEC system with layered ARQ. Although feedback is normally problematic in broadcast situations, ARQ is simulated by having the receivers subscribe and unsubscribe to the delayed channel coding layers to receive missing information. This pseudo-ARQ scheme avoids an implosion of repeat requests at the sender, and is scalable to an unlimited number of receivers. We show gains of up to 18 dB on channels with 20% loss over systems without error control, and additional gains of up to 13 dB when FEC is augmented by pseudo-ARQ in a hybrid system. The hybrid system is controlled by an optimal policy for a Markov decision process.<\/p>\n","protected":false},"excerpt":{"rendered":"

We consider the problem of joint source\/channel coding of real-time sources, such as audio and video, for the purpose of multicasting over the Internet. The sender injects into the network multiple source layers and multiple channel (parity) layers, some of which are delayed relative to the source. Each receiver subscribes to the number of source […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-155218","msr-research-item","type-msr-research-item","status-publish","hentry","msr-locale-en_us"],"msr_publishername":"Institute of Electrical and Electronics Engineers, Inc.","msr_edition":"Communication Theory Workshop","msr_affiliation":"","msr_published_date":"2000-03-28","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"IEEE","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"211197","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"ChouMWM99.ppt","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/ChouMWM99.ppt","id":211197,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":211197,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/ChouMWM99.ppt"}],"msr-author-ordering":[{"type":"text","value":"S. Mehrotra","user_id":0,"rest_url":false},{"type":"text","value":"Philip A. Chou","user_id":0,"rest_url":false},{"type":"text","value":"Alexander E. Mohr","user_id":0,"rest_url":false},{"type":"text","value":"Albert Wang","user_id":0,"rest_url":false},{"type":"user_nicename","value":"sanjeevm","user_id":33516,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=sanjeevm"},{"type":"user_nicename","value":"pachou","user_id":33176,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=pachou"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/155218"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":2,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/155218\/revisions"}],"predecessor-version":[{"id":541508,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/155218\/revisions\/541508"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=155218"}],"wp:term":[{"taxonomy":"msr-content-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-content-type?post=155218"},{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=155218"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=155218"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=155218"},{"taxonomy":"msr-product-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-product-type?post=155218"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=155218"},{"taxonomy":"msr-platform","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-platform?post=155218"},{"taxonomy":"msr-download-source","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-download-source?post=155218"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=155218"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=155218"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=155218"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=155218"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=155218"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=155218"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=155218"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}