Content-adaptive traffic prioritization of spatio-temporal scalable video for robust communications over QoS-provisioned 802.11e networks

In this work a low complexity traffic prioritization strategy to transmit H.264 scalable video coding (SVC) video over 802.11e wireless networks is presented (the approach applies to any DiffServ-like network). The distinguishing feature of the proposed strategy is the ability to adapt the amount of error protection to the changing characteristics of the video content. First, we estimate the perceptual impact of data losses in the different types of enhancement layers, i.e., temporal or spatial, for a large set of H.264/SVC videos. The experiments show that perceptual impairments are highly correlated with the level of motion activity in the video sequence. Then, we propose a content-adaptive traffic prioritization strategy based on the identification of the most important parts of the enhancement layers of the video sequence by means of a low complexity macroblock analysis process. The prioritization algorithm is tested by simulating a realistic 802.11e ad hoc network scenario. Simulation results show that the proposed traffic prioritization strategy consistently outperforms, particularly for dynamic video sequences, fixed a priori approaches, as well as a traditional FEC-based UEP strategy.