| Abstract: | Video transmission over wireless channels is affected by channel-induced packet losses. Distortion due to channel errors can be alleviated by applying forward error correction. Aggregating H.264/AVC slices to form video packets with sizes adapted to their importance can also improve transmission reliability. Larger packets are more likely to be in error but smaller packets require more overhead. We present a cross-layer dynamic programming (DP) approach to minimize the expected received video distortion by jointly addressing the priority-adaptive packet formation at the application layer and rate compatible punctured convolutional (RCPC) code rate allocation at the physical layer for prioritized slices of each group of pictures (GOP). Some low priority slices are also discarded to improve protection to more important slices and meet the channel bit-rate limitations. We propose two schemes. Our first scheme carries out joint optimization for all slices of a GOP at a time. The second scheme extends our cross-layer DP-based approach to slices of each frame by predicting the expected channel bit budget per frame for live streaming. The prediction uses a generalized linear model developed over the cumulative mean squared error per frame, channel SNR, and normalized compressed frame bit budget. The parameters are determined over a video dataset that spans high, medium and low motion complexity. The predicted frame bit budget is used to derive the packet sizes and corresponding RCPC code rates for live transmission using our DP-based approach. Simulation results show that both proposed schemes significantly improve the received video quality over contemporary error protection schemes. |
