Mohamed Hefeeda Multiplexing of Variable Bitrate Scalable Video for Mobile Broadcast Networks Project Presentation Farid Molazem Cmpt 820 Fall 2010 School of Computing Science Simon Fraser University

Mohamed Hefeeda Outline  High level description of the problem  Overview of scalable video coding  Formulation of the problem  Problem solution  Evaluation and results

Mohamed Hefeeda High level description of the problem  The problem we study here is broadcasting several variable bitrate video streams to a large number of mobile receivers while maximizing performance metrics of bandwidth utilization and energy saving  Challenges -Variability in the bitrates of video streams -Small buffer sizes of mobile receivers -Energy constraints for mobile devices

Mohamed Hefeeda Scalable Video Coding  Scalable video coding -Temporal scalability -Spatial scalability -Quality scalability

Mohamed Hefeeda Quality Scalability  Quality scalability could be considered as a special case of spatial scalability  We could have -Fine Grain Scalability -Coarse Grain Scalability -Medium Grain Scalability

Mohamed Hefeeda Problem Formulation  Problem: Broadcasting S scalable video streams from a base station to a large number of mobile receivers over a wireless medium  Notation: -There are S video streams -Each frame video stream s has a base layer and MGS layers -Each video stream has I frames - Indicates the size of layer k of frame i of stream s -Each stream is coded at F frame-per-second Frame i of stream s Base layer

Mohamed Hefeeda Problem Formulation  Bandwidth Utilization -The fraction of video frames received at the decoder before their decoding deadline  Energy Saving: -The fraction of time the receivers can put their wireless receivers into sleep -We use the average energy saving among all video streams

Mohamed Hefeeda Problem Formulation  The average quality of all transmitted frames is shown by -We use peak-signal-to-noise-ration (PSNR) as a quality metric

Mohamed Hefeeda Problem Solution time

Mohamed Hefeeda Problem Solution -Second Step: Consider only base layer of video streams Add burst to S2 until it reached threshold Now we add back the quality layers as long as we have available bandwidth in our rescheduling window time s1 s2 Below threshold Rescheduling window

Mohamed Hefeeda Problem Solution time s1 s2 Below threshold Rescheduling window

Mohamed Hefeeda Problem Solution -Second Step:  We have a number of frames  Each frame has a number of quality layers  Selecting each quality layer consumes some space and provides some quality value  Which quality layers to choose? »0-1 multiple choice knapsack »NP-Complete

Mohamed Hefeeda Problem Solution

Mohamed Hefeeda Evaluation  Settings -We set the modulator to use 16-QAM (Quadrature Amplitude Modulation) -10MHz radio channel -Overhead To=100ms  Video streams -16 video streams of different categories of: sport, tv game show, documentray, talk show and have very different visual characteristics -Bitrates ranging from 250 to 768 kbps -We created video streams with different MGS layers and the trace file for each stream using “BitStreamExtractorStatic” tool provided by JSVM -We used “PSNRStatic” to determine the PSNR value of each MGS layer of each video stream

Mohamed Hefeeda Results  Dropped Frame

Mohamed Hefeeda Results  Resulted Quality

Mohamed Hefeeda Conclusions  Having a small lookahead window, we can have an approximation algorithm to reduce dropped frame using quality scalability characteristics of scalable video streams  Operator can adjust the chance of dropping frame by adjusting the threshold for buffer levels -Reducing the threshold lowers the chance of dropping frames at a cost of loosing some quality in video frames

Mohamed Hefeeda Thanks You