Technical Program

Paper Detail

Paper IDS.3.4
Paper Title New Formulas of Ergodic Feedback Capacity of AGN Channels Driven by Stable and Unstable Autoregressive Noise
Authors Christos Kourtellaris, Charalambos D. Charalambous, University of Cyprus, Cyprus; Sergey Loyka, University of Ottawa, Canada
Session S.3: Channels with Feedback
Presentation Lecture
Track Shannon Theory
Manuscript  Click here to download the manuscript
Virtual Presentation  Click here to watch in the Virtual Symposium
Abstract In this paper we characterize the feedback capacity of Additive Gaussian Noise (AGN) channels driven by stable and unstable autoregressive noise, for time-invariant feedback codes (channel input distributions). For stable (resp. unstable) channel noise we identify necessary and sufficient conditions for the optimal input process to induce asymptotic stationarity and ergodicity of the channel output (resp. innovations) process. We call this the {\emph{ergodic feedback capacity}}. From our characterization follows the surprising result: for a time-invariant unit memory Gaussian autoregressive noise AR($c$), $c\in (-\infty,\infty)$, (i) feedback does not increase capacity for the region with $c\in (-1,1)$ and certain unstable $c$, and total transmit power $\kappa \in [0,\infty)$, and (ii) feedback increases capacity for the compliment of the region of values of $(c, \kappa)$, not covered in (i).

Plan Ahead


2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

Visit Website!