Distortion and Deadline Aware Packet Scheduling for Video Streaming over Wireless

Most of current wireless packet scheduling algorithms aim at maximizing overall system throughput or achieving a certain type of fairness among mobile users. However, these content-independent algorithms can not be applied to wireless video transmission because different video packets have different levels of contribution to the overall video quality at the receiver side. Fully exploring the differences between the video packets and accurate predicting the transmission distortion caused by lost video packets can significantly improve the performance of video streaming over resource-constrained wireless networks. In this paper, a packet-level transmission distortion model is proposed to predict the quality degradation of decoded videos by lost video packets, the packet-level deadline is defined to extend the model. Based on this packet-level transmission distortion model and packet-level deadline extended model, a gradient-based distortion and deadline aware scheduling algorithm is proposed, which prioritizes the transmissions of different users by considering distortion impact, deadline requirements and fully exploit the flexibility of resource allocation provided by the Orthogonal Frequency Division Multiplexing (OFDM) technology in terms of time, frequency and power. The experimental results demonstrate that the proposed algorithm outperforms the content-independent algorithms with a gain of as much as 4.3 dB in terms of average Peak Signal-to-Noise Ratio (PSNR).