Channel Aware Multiuser Scalable Video Streaming Over Lossy Under-Provisioned Channels: Modeling and Analysis

TitleChannel Aware Multiuser Scalable Video Streaming Over Lossy Under-Provisioned Channels: Modeling and Analysis
Publication TypeJournal Article
Year of Publication2008
AuthorsMansour, H., V. Krishnamurthy, and P. Nasiopoulos
JournalMultimedia, IEEE Transactions on
Pagination1366 -1381
Date Publishednov.
Keywords3GPP network simulator, bandwidth-intensity, channel aware multiuser scalable video streaming, delay-aware nonstationary rate-allocation streaming policies, delay-sensitivity, hierarchical predictive video coders, latency problems, loss-distortion model, loss-tolerance, media-aware multiuser video streaming strategies, multiuser channels, noise figure 1.65 dB to 2 dB, packet loss rates, packet losses, unequal erasure protection, video coding, video streaming, wireless channels, wireless video streaming applications

In this paper, we analyze the performance of media-aware multiuser video streaming strategies in capacity limited wireless channels suffering from latency problems and packet losses. Wireless video streaming applications are characterized by their bandwidth-intensity, delay-sensitivity, and loss-tolerance. Our main contributions include (i) a rate-minimized unequal erasure protection (UXP) scheme, (ii) an analytical expression for packet delay and play-out deadline of UXP protected scalable video, (iii) a loss-distortion model for hierarchical predictive video coders with picture copy concealment, (iv) an analysis of the performance and complexity of delay-aware, capacity-aware, and optimized UXP streaming scenarios, and (v) we show that the use of unequal error protection causes a rate-constrained optimization problem to be nonconvex. Performance evaluations using a 3GPP network simulator show that, for different channel capacities and packet loss rates, delay-aware nonstationary rate-allocation streaming policies deliver significant gains which range between 1.65 dB to 2 dB in average Y-PSNR of the received video streams over delay-unaware strategies. These gains come at a cost of increased offline computation which is performed prior to the start of the streaming session or in batches during transmission and therefore, do not affect the run-time performance of the streaming system.


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