Wireless Channel Modeling Based on Finite-state Markov Model

In this paper, a wireless channel is viewed as a heterogeneous network in the time domain, and an adaptive video transmission scheme for H.264 scalable video over wireless channels modeled as a finite-state Markov chain processes is presented. In order to investigate the robustness of adaptive video transmission for H.264 scalable video over wireless channels, statistical channel models can be employed to characterize the error and loss behavior of the video transmission. Among various statistical channel models, a finite-state Markov model has been considered as suitable for both wireless links as Rayleigh fading channels and wireless local area networks as a combination of bit errors and packet losses. The H.264 scalable video coding enables the rate adaptive source coding and the feedback of channel parameters facilitates the adaptive channel coding based on the dynamics of the channel behavior. As a result, we are able to develop a true adaptive joint source and channel based on instantaneous channel estimation feedback. Preliminary experimental results demonstrate that the estimation of the finite-state Markov channel can be quite accurate and the adaptive video transmission based on channel estimation is able to perform significantly better than the simple channel model in which only average bit error rate is used for joint source and channel coding design.