Sequential coding of Gauss-Markov sources with packet erasures and feedback

Anatoly Khina, Victoria Kostina, Ashish Khisti, Babak Hassibi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations


We consider the problem of sequential transmission of Gauss-Markov sources. We show that in the limit of large spatial block lengths, greedy compression with respect to the squared error distortion is optimal; that is, there is no tension between optimizing the distortion of the source in the current time instant and that of future times. We then extend this result to the case where at time t a random compression rate rt is allocated independently of the rate at other time instants. This, in turn, allows us to derive the optimal performance of sequential coding over packet-erasure channels with instantaneous feedback. For the case of packet erasures with delayed feedback, we connect the problem to that of compression with side information that is known at the encoder and may be known at the decoder - where the most recent packets serve as side information that may have been erased, and demonstrate that the loss due to a delay by one time unit is rather small.
Original languageEnglish (US)
Title of host publication2017 IEEE Information Theory Workshop (ITW)
Number of pages2
ISBN (Print)9781509030972
StatePublished - Feb 1 2018
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-06-28
Acknowledgements: The work of A. Khina has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 708932. The work of V. Kostina was supported in part by the National Science Foundation under Grant CCF-1566567. Ashish Khisti was supported by the Canada Research Chairs Program. The work of B. Hassibi was supported in part by the National Science Foundation under grants CNS-0932428, CCF-1018927, CCF-1423663 and CCF-1409204, by a grant from Qualcomm Inc., by NASA’s Jet Propulsion Laboratory through the President and Director’s Fund, by King Abdulaziz University, and by King Abdullah University of Science and Technology.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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