Perceptual quality driven cross-layer optimization for wireless video streaming

The traditional cross-layer model for video streaming can achieve significant improvement to the end-to-end video quality. However, the video quality measurement in terms of sum of squared error (SSE) in the model does not always correlate well with the perception of the human visual system. In this paper, we propose a perceptual quality driven cross-layer optimization scheme based on the structural similarity (SSIM) index for wireless video streaming. The H.264/AVC encoding parameters on the application layer and the modulation and channel coding modes on the physical layer are mainly considered to optimize the end-to-end perceptual video quality. In order to decrease the computation complexity, a low complexity optimization algorithm based on the rate-quantization (R-Q) model is proposed to reduce the range of the candidate optimization parameters. Experimental results show that the proposed SSIM-based cross-layer optimization scheme achieves better perceptual quality than the SSE-based cross-layer optimization scheme, and the proposed low complexity optimization algorithm can achieve about 62% computation decrease compared to the conventional exhaustive searching algorithm with little loss in perceptual quality.