Abstract
We propose an application-layer forward error correction (AL-FEC) code rate allocation scheme to maximize the quality of experience (QoE) of a video multicast. The allocation dynamically assigns multicast clients to the quality layers of a scalable video bitstream, based on their heterogeneous channel qualities and video playback capabilities. Normalized mean opinion score (NMOS) is employed to value the client's quality of experience across various possible adaptations of a multilayer video, coded using mixed spatial-temporal-amplitude scalability. The scheme provides assurance of reception of the video layers using fountain coding and effectively allocates coding rates across the layers to maximize a multicast utility measure. An advantageous feature of the proposed scheme is that the complexity of the optimization is independent of the number of clients. Additionally, a convex formulation is proposed that attains close to the best performance and offers a reliable alternative when further reduction in computational complexity is desired. The optimization is extended to perform suppression of QoE fluctuations for clients with marginal channel qualities. The scheme offers a means to trade-off service utility for the entire multicast group and clients with the worst channels. According to the simulation results, the proposed optimization framework is robust against source rate variations and limited amount of client feedback.
Highlights
1.1 Motivation Multimedia delivery systems can be optimized to maximize the overall throughput or to satisfy client quality of experience (QoE) demands (QoS-guaranteed)
Compared to the previous multicast optimization techniques based on fountain codes in [8, 10, 35], our work considers clients with heterogeneous channels and video-playback quality demands and benefits from a simple yet accurate model [36] of the client decoding outage probability
6 Conclusions Considering heterogeneity of client channels and their terminal capabilities, we introduced a QoE optimization framework for video multicast that benefits from the flexibility offered by scalable video coding and fountain coding
Summary
1.1 Motivation Multimedia delivery systems can be optimized to maximize the overall throughput (best effort) or to satisfy client quality of experience (QoE) demands (QoS-guaranteed). This paper is concerned with an efficient application of fountain codes as an application-layer FEC (AL-FEC) code to meet the QoE demands of video multicast clients with heterogeneous channels and video quality requirements. Our problem provides an answer to the question: given an application-layer multicast service bandwidth, a population of clients with heterogeneous end-to-end channels and devices (with different video playback capabilities), determine how best to provision fountain codes across the video layers in order to serve as many clients as possible while meeting their video perceptual-quality demands. Compared to the previous multicast optimization techniques based on fountain codes in [8, 10, 35], our work considers clients with heterogeneous channels and video-playback quality demands and benefits from a simple yet accurate model [36] of the client decoding outage probability.
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