cient Transport of Real - Time VBR Video over ATM

This paper presents a novel approach to dynamic transmission bandwidth allocation for transport of real-time variable-bit-rate video in ATM networks. Video traac statistics are measured in the frequency domain: the low frequency signal captures the slow time-variation of consecutive scene changes while the high frequency signal exhibits the feature of strong frame autocorrelation. Our queueing study indicates that the video transmission bandwidth in a nite-buuer system is essentially characterized by the low frequency signal. We further observe in typical JPEG/MPEG video sequences that the time scale of video scene changes is in the range of a second or longer, which localizes the low frequency video signal in a well-deened low frequency band. Hence, in a network design it is feasible to implement dynamic allocation of video transmission bandwidth using on-line observation and prediction of scene changes. Two prediction schemes are examined: recursive least square method and time delay neural network method. A time delay neural network with low-complexity high-order architecture, called \Pi-Sigma Network", is successfully used to predict scene changes. The overall dynamic bandwidth allocation scheme presented in this paper is shown to be promising and practically feasible in obtaining eecient transmission of real-time video traac. video transmission bandwidth Figure 1: A single-link nite-buuer system.