Convex Optimization
Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels
IEEE Transactions on Signal Processing
IEEE Transactions on Multimedia
Joint selection of source and channel rate for VBR video transmission under ATM policing constraints
IEEE Journal on Selected Areas in Communications
Optimized Rate-Distortion Extraction With Quality Layers in the Scalable Extension of H.264/AVC
IEEE Transactions on Circuits and Systems for Video Technology
Mobile Video Transmission Using Scalable Video Coding
IEEE Transactions on Circuits and Systems for Video Technology
Overview of the Scalable Video Coding Extension of the H.264/AVC Standard
IEEE Transactions on Circuits and Systems for Video Technology
Optimal adaptive channel scheduling for scalable video broadcasting over MIMO wireless networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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We propose a framework for multicasting layers of scalable video over a broadcast channel to multiple users simultaneously. The framework ensures that all users receive the content, but at differentiated levels of quality depending on channel conditions. A coding scheme well-suited to this purpose is Scalable Video Coding (SVC). In particular, we employ medium-grain scalability (MGS), which allows us to generate quality-scalable layers from a single video sequence. For transport, we assume that both the transmitter and end-users are equipped with multiple-input multiple-output (MIMO) transceivers. The transmitter employs the zero-forcing (ZF) precoding technique, which yields good performance with low complexity. With these assumptions, the scheme proposed here computes a block-diagonal ZF-precoder at fixed intervals, subject to a power constraint at the transmitter. Crucially, the algorithm assigns quality-scalable layers of video to the end-users jointly with precoder computation. The framework also ensures that delay and buffer constraints are met, which is necessary for real-time video. In terms of solution approach, the problem turns out to be a difficult mixed-integer nonlinear optimization problem.