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We propose an application-layer forward error correction (AL-FEC) code rateallocation scheme to maximize the quality of experience (QoE) of a videomulticast. The allocation dynamically assigns multicast clients to the qualitylayers of a scalable video bitstream, based on their heterogeneous channelqualities and video playback capabilities. Normalized mean opinion score (NMOS)is employed to value the client's quality of experience across various possibleadaptations of a multilayer video, coded using mixed spatial-temporal-amplitudescalability. The scheme provides assurance of reception of the video layersusing fountain coding and effectively allocates coding rates across the layersto maximize a multicast utility measure. An advantageous feature of theproposed scheme is that the complexity of the optimization is independent ofthe number of clients. Additionally, a convex formulation is proposed thatattains close to the best performance and offers a reliable alternative whenfurther reduction in computational complexity is desired. The optimization isextended to perform suppression of QoE fluctuations for clients with marginalchannel qualities. The scheme offers a means to trade-off service utility forthe entire multicast group and clients with the worst channels. According tothe simulation results, the proposed optimization framework is robust againstsource rate variations and limited amount of client feedback.

QoE Optimization of Video Multicast with Heterogeneous Channels and Playback Requirements