Transmission distortion analysis for real-time video encoding and streaming over wireless networks

A major challenge in video encoding and transmission over wireless networks is that the channel is error-prone while the compressed video data is highly sensitive to errors. The transmission errors will cause decoding failure at the receiver side. More importantly, the transmission errors introduced in one video frame will propagate to its subsequent frames along the motion prediction path and significantly degrade video presentation quality. This type of picture distortion is called transmission distortion. In this work, we propose a control system approach to transmission distortion modeling. More specifically, we consider the wireless video transmission and decoding system as a linear system with the transmission errors as system input and the transmission distortion as output. We study the fading behavior of the impulse transmission distortion. We analyze the low-pass filtering behavior of video encoders and develop a scheme to estimate the instantaneous transmission distortion. Our extensive simulation results demonstrate that the proposed transmission distortion model is accurate and robust. In addition, it has very low computational complexity. More importantly, because it is a predictive model, it allows the encoder to predict the transmission distortion even before the video is compressed and transmitted; This type of transmission distortion model has important applications in resource allocation and performance optimization in real-time wireless video communication.