A joint source-channel coding approach to network transport on digital video

The use of forward error-control (FEC) coding, possibly in conjunction with passive-error recovery techniques, has emerged as a promising approach for real-time video transport over ATM networks for cell loss recovery and/or bit error correction, such as might be required for wireless links. Although FEC provides cell-loss recovery, through its erasure correcting capabilities, it also introduces transmission overhead which can possibly cause additional cell losses. A joint source-channel coding methodology is described to maximize the number of video sources multiplexed at a given quality of service (QoS), measured in terms of overall reproduced video quality. The transport channel is modeled as a block interference channel (BIC) and the multiplexer as a single server, deterministic service, finite buffer supporting N users. Based upon an information-theoretic characterization of the BIC and large deviation bounds on the buffer overflow probability, we describe a methodology that provides theoretically achievable upper limits on the number of sources multiplexed at a given level of performance. Performance of a specific coding technique using an MPEG-2 source encoder and interlaced non-binary Reed-Solomon (RS) channel codes is illustrated and shown to approach the information-theoretic predictions with increasing levels of complexity.

[1]  Suresh Rai,et al.  Analyzing packetized voice and video traffic in an ATM multiplexer , 1998, 1998 IEEE International Performance, Computing and Communications Conference. Proceedings (Cat. No.98CH36191).

[2]  Nick G. Duffield,et al.  Large deviations, the shape of the loss curve, and economies of scale in large multiplexers , 1995, Queueing Syst. Theory Appl..

[3]  R. Gallager.  Information Theory and Reliable Communication , 1968 .

[4]  Wayne E. Stark,et al.  Channels with block interference , 1984, IEEE Trans. Inf. Theory.

[5]  James W. Modestino,et al.  Use of FEC coding to improve statistical multiplexing performance for video transport over ATM networks , 1998, Electronic Imaging.

[6]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[7]  R. Weber,et al.  Buffer overflow asymptotics for a buffer handling many traffic sources , 1996, Journal of Applied Probability.

[8]  Jacky Guibert,et al.  Large Deviations Approximations for Fluid Queues Fed by a Large Number of On/Off Sources , 1995, IEEE J. Sel. Areas Commun..

[9]  A. Adas,et al.  Traffic models in broadband networks , 1997, IEEE Commun. Mag..

[10]  Dan Keun Sung,et al.  Two-state MMPP modeling of ATM superposed traffic streams based on the characterization of correlated interarrival times , 1995, Proceedings of GLOBECOM '95.

[11]  Naoaki Yamanaka,et al.  Overview of measurement-based connection admission control methods in ATM networks , 1999, IEEE Communications Surveys & Tutorials.

[12]  Rae-Hong Park,et al.  Connection admission control for video traffic using modified equivalent capacity , 1995, Proceedings of GLOBECOM '95.

[13]  B. Melamed,et al.  Traffic modeling for telecommunications networks , 1994, IEEE Communications Magazine.

[14]  H. Heffes,et al.  A class of data traffic processes — covariance function characterization and related queuing results , 1980, The Bell System Technical Journal.

[15]  David M. Lucantoni,et al.  A Markov Modulated Characterization of Packetized Voice and Data Traffic and Related Statistical Multiplexer Performance , 1986, IEEE J. Sel. Areas Commun..