Content-aware packet scheduling for multiuser scalable video delivery over wireless networks

Ehsan Maani*, Peshala V. Pahalawatta, Randall Berry, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Wireless video transmission is prone to potentially low data rates and unpredictable degradations due to timevarying channel conditions. Such degradations are difficult to overcome using conventional video coding techniques. Scalable video coding offers a flexible bitstream that can be dynamically adapted to fit the prevailing channel conditions. Advances in scalable video compression techniques, such as the newly adopted scalable extension of H.264/AVC, as well as recent advances in wireless access technologies offer possibilities for tackling this challenge. In this paper, a content-aware scheduling and resource allocation scheme is proposed, that uses a gradient-based scheduling framework in conjunction with scalable video coding techniques to provide multiple high quality video streams over a range of operating conditions to multiple users. Simulation results show that the proposed scheme performs better than conventional content-independent scheduling techniques.

Original languageEnglish (US)
Title of host publicationApplications of Digital Image Processing XXXII
DOIs
StatePublished - 2009
EventApplications of Digital Image Processing XXXII - San Diego, CA, United States
Duration: Aug 3 2009Aug 5 2009

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7443
ISSN (Print)0277-786X

Other

OtherApplications of Digital Image Processing XXXII
Country/TerritoryUnited States
CitySan Diego, CA
Period8/3/098/5/09

Keywords

  • Cross-layer design
  • Scalable video coding
  • Wireless video streaming

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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