Trade-offs in bit-rate allocation for wireless video streaming
IEEE Transactions on Multimedia - Special issue on quality-driven cross-layer design for multimedia communications
Adaptive video streaming with long term feedbacks
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
On-line learning and optimization for wireless video transmission
IEEE Transactions on Signal Processing
A theoretical framework for interaction measure and sensitivity analysis in cross-layer design
ACM Transactions on Modeling and Computer Simulation (TOMACS)
QoE-based opportunistic transmission for video broadcasting in heterogeneous circumstance
Proceedings of the 20th ACM international conference on Multimedia
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Demand for multimedia services, such as video streaming over wireless networks, has grown dramatically in recent years. The downlink transmission of multiple video sequences to multiple users over a shared resource-limited wireless channel, however, is a daunting task. Among the many challenges in this area are the time-varying channel conditions, limited available resources, such as bandwidth and power, and the different transmission requirements of different video content. This work takes into account the time-varying nature of the wireless channels, as well as the importance of individual video packets, to develop a cross-layer resource allocation and packet scheduling scheme for multiuser video streaming over lossy wireless packet access networks. Assuming that accurate channel feedback is not available at the scheduler, random channel losses combined with complex error concealment at the receiver make it impossible for the scheduler to determine the actual distortion of the sequence at the receiver. Therefore, the objective of the optimization is to minimize the expected distortion of the received sequence, where the expectation is calculated at the scheduler with respect to the packet loss probability in the channel. The expected distortion is used to order the packets in the transmission queue of each user, and then gradients of the expected distortion are used to efficiently allocate resources across users. Simulations show that the proposed scheme performs significantly better than a conventional content-independent scheme for video transmission.