Information Velocity of Cascaded Gaussian Channels With Feedback

Elad Domanovitz, Anatoly Khina, Tal Philosof, Yuval Kochman

Research output: Contribution to journalArticlepeer-review


We consider a line network of nodes, connected by additive white noise channels, equipped with local feedback. We study the velocity at which information spreads over this network. For transmission of a data packet, we give an explicit positive lower bound on the velocity, for any packet size. Furthermore, we consider streaming, that is, transmission of data packets generated at a given average arrival rate. We show that a positive velocity exists as long as the arrival rate is below the individual Gaussian channel capacity, and provide an explicit lower bound. Our analysis involves applying pulse-amplitude modulation to the data (successively in the streaming case), and using linear mean-squared error estimation at the network nodes. For general white noise, we derive exponential error-probability bounds. For single-packet transmission over channels with (sub-)Gaussian noise, we show a doubly-exponential behavior, which reduces to the celebrated Schalkwijk–Kailath scheme when considering a single node. Viewing the constellation as an “analog source”, we also provide bounds on the exponential decay of the mean-squared error of source transmission over the network.

Original languageEnglish
Pages (from-to)1
Number of pages1
JournalIEEE Journal on Selected Areas in Information Theory
StateAccepted/In press - 2024

Bibliographical note

Publisher Copyright:


  • Channel capacity
  • Channel estimation
  • Electronic mail
  • Error probability
  • Noise
  • Relays
  • Transmitters


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