A deadlineaware transmission framework for H.264AVC video over IEEE 802.11e EDCA wireless networks One of the most challenging issues in video transmission over wireless networks is to address the rigid time bounded constraint for video delivery. We propose in this paper a deadlineaware transmission framework (DATF) for video over IEEE 802.11e EDCA wireless networks. In this new framework, we estimate the deadline for time bounded video delivery for each packet in queues at MAC layer according to the sequence number of a frame a given video data packet belonging to as well as the current network delay. Then, the MAC layer determines whether a packet should be sent or should be dropped based on the estimated deadline information. To accomplish the scheme of DATF, we propose to modify the mapping scheme in IEEE 802.11e EDCA to facilitate unequal deadline requirement of video packets. Instead of mapping all video packets into class AC_VI, which is defined for video data in IEEE 802.11e EDCA, we differentiate video packets further based on the dependency characteristics of a given frame type. The proposed DATF scheme has been implemented with NS2 simulation based on the scenario of wiredcumwireless network architecture. We compare the proposed approach with several competing schemes and the simulation results show that the proposed scheme outperforms these competing schemes in terms of both wireless networking metrics and received video quality.

Crosslayer optimization for wireless video communication With the rapid growth of wireless networks and increasing popularity of portable video devices, wireless video communication is poised to become the enabling technology for many multimedia applications over wireless networks. Realtime wireless video transmission typically has requirements on quality of service (QoS). However, wireless channels are unreliable and the channel capacities are timevarying, which may cause severe degradation to video presentation quality. In addition, for portable devices, video compression and wireless transmission are tightly coupled through the constraints on data rate, power, and delay. These issues make it particularly challenging to design an efficient realtime video compression and wireless transmission system on a portable device. In this paper, we take a crosslayer approach to this problem; our objective is to maximize the video quality under the constraints of resource and delay. Specifically, we minimize the endtoend video distortion under the constraints of resource and delay, over the parameters in physical, link, and application (video) layers. This formulation is general and capable of capturing the fundamental aspects of the design of wireless video communication systems. Based on this formulation, we study how the resources could be intelligently allocated to maximize the video quality and analyze the performance limits of the wireless video communication system under resource constraints.