Viewing Impaired Video Transmissions From a Modeling Perspective Oliver Hohlfeld, Florin Ciucu Technische Universitaet Berlin Deutsche Telekom Laboratories Berlin, Germany { oliver, orin} @ net.t-labs.tu-berlin.de can introduce even larger time-scales. While losing a single macroblock can have a minor impact by a ecting only a small fraction of the image, losing a parameter set can have a severe e ect on the decoding process. This consideration suggests to focus on the loss process over multiple time-scales rather than on matching burst and gap length distributions. To address this observation, this paper uses an M -state Markov chain to generate loss traces for impairing video transmissions. To this end, Section 2 provides a general result for M -state Markov chains to describe the distribution of the packet losses over multiple time-scales using secondorder statistics. By using moment matching, 2-state Markov models are tted to a wireless Digital Video Broadcasting (DVB-H) loss trace. Then Section 3 presents numerical results which illustrate that the visual impairment patterns depend on the chosen modeling technique. For future work we plan to investigate relevant time-scales for the tting process. Moreover, we plan to evaluate whether increasing the number of states of the underlying Markov
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Viewing impaired video transmissions from a modeling perspective
Hohlfeld, Oliver; Ciucu, Florin
Follow ACM SIGMETRICS Performance Evaluation Review
, Volume 37 (2)
Association for Computing Machinery – Oct 16, 2009
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