This document describes a quality-differentiated video multicast scheme for multirate wireless networks called QDM. QDM aims to provide heterogeneous clients with differentiated video qualities matching their channel conditions. It first proposes a rate scheduling model to select the optimal transmission bitrate for each video frame to maximize total visual quality subject to minimum quality guarantees. It then presents QDM, a practical protocol that constructs a cluster-based structure to characterize heterogeneity and adapts transmission rates based on video quality perceived by representative cluster heads. Simulation results show QDM can efficiently adapt to network dynamics and variable video bitrates, producing a 2-5 dB gain in average video quality over leader-based approaches.

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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 leaderbased 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-visualquality-guaranteed constraint.
We present a practical and easy-to-implement protocol, called QDM, which constructs a clusterbased 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.