This document discusses a quality-differentiated video multicast scheme for multirate wireless networks. It proposes a rate scheduling model that selects the optimal transmission bitrate for each video frame to maximize total visual quality while guaranteeing a minimum quality. It also presents QDM, a practical protocol that constructs cluster-based structures to characterize heterogeneity and adapts the transmission bitrate based on video quality perceived by cluster heads. Experimental results show QDM can efficiently adapt to network dynamics and variable bitrates, producing a gain of 2-5 dB in average video quality compared to leader-based approaches.

1. QUALITY-DIFFERENTIATED VIDEO MULTICAST IN MULTIRATE
WIRELESS NETWORKS
ABSTRACT:
Adaptation of modulation and transmission bit-rates for video multicast in a multirate wireless
network is a challenging problem because of network dynamics, variable video bit-rates, and
heterogeneous clients who may expect differentiated video qualities. Prior work on the leader-
based schemes selects the transmission bit-rate that provides reliable transmission for the node
that experiences the worst channel condition.
However, this may penalize other nodes that can achieve a higher throughput by receiving at a
higher rate. In this work, we investigate a rate-adaptive video multicast scheme that can provide
heterogeneous clients differentiated visual qualities matching their channel conditions. We first
propose a rate scheduling model that selects the optimal transmission bitrate for each video
frame to maximize the total visual quality for a multicast group subject to the m inimum-visual-
quality-guaranteed constraint.
We present a practical and easy-to-implement protocol, called QDM, which constructs a cluster-
based structure to characterize node heterogeneity and adapts the transmission bit-rate to network
dynamics based on video quality perceived by the representative cluster heads. Since QDM
selects the rate by a sample-based technique, it is suitable for real-time streaming even without
any preprocess. We show that QDM can adapt to network dynamics and variable video-bit rates
efficiently, and produce a gain of 2-5 dB in terms of the average video quality as compared to the
leader-based approach.
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