SSIM-based error-resilient cross-layer optimization for wireless video streaming.

The traditional Sum of Squared Error (SSE)-based cross-layer optimization has been shown to be an effective way to improve the quality of service for wireless video streaming. However, recent research works show that the SSE-based optimization metric does not always provide the video distortion measurement that matches well with the video quality degradation observed by the human vision system. Taking advantage of the Structural SIMilarity (SSIM) metric in measuring the video perceptual quality, a SSIM-based error-resilient cross-layer optimization scheme is proposed to improve the perceptual quality for the real-time wireless video streaming in this paper. Besides the video data rate adjustment and the link adaption including the Modulation and Coding Scheme (MCS) selection, the error-resilient Rate-Distortion Optimization (RDO) for each encoding unit is introduced into the cross-layer optimization process to ensure that the video data are transmitted efficiently and reliably over the time-varying wireless channel. In addition, to ensure that cross-layer optimization scheme is more practical, a low-complexity optimal parameter selection algorithm that exploits the MCS-SNR relationship and the Rate-Quantization (R-Q) model is proposed. Experimental results show that significant performance improvements in terms of the perceptual video quality and the computational complexity are achieved for the proposed cross-layer optimization scheme.