Dynamic resource allocation for MGS H.264/AVC video transmission over link-adaptive networks

  • Authors:

  • Hassan Mansour;Yaser Pourmohammadi Fallah;Panos Nasiopoulos;Vikram Krishnamurthy

  • Affiliations:

  • Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada;Institute of Transportation Studies, University of California, Berkeley, Berkeley, CA;Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada;Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada

  • Venue:
  • IEEE Transactions on Multimedia
  • Year:
  • 2009

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Abstract

In this paper, we address the problem of efficiently allocating network resources to support multiple scalable video streams over a constrained wireless channel. We present a resource allocation framework that jointly optimizes the operation of the link adaptation scheme in the physical layer (PHY), and that of a traffic control module in the network or medium access control (MAC) layer in multirate wireless networks, while satisfying bandwidth/capacity constraints. Multirate networks, such as IEEE 802.16 or IEEE 802.11, adjust the PHY coding and modulation schemes to maintain the reliability of transmission under varying channel conditions. Higher reliability is achieved at the cost of reduced PHY bit-rate which in turn necessitates a reduction in video stream bit-rates. The rate reduction for scalable video is implemented using a traffic control module. Conventional solutions operate unaware of the importance and loss tolerance of data and drop the higher layers of scalable video altogether. In this paper, we consider medium grain scalable (MGS) extension of H.264/AVC video and develop new rate and distortion models that characterize the coded bitstream. Performance evaluations show that our proposed framework results in significant gains over existing schemes in terms of average video PSNR that can reach 3 dB in some cases for different channel SNRs and different bandwidth budgets.