2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | S.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
