2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | S.3.7 | ||
| Paper Title | From Feedback Capacity to Tight Achievable Rates without Feedback for AGN Channels with 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 employ the information structures of optimal channel inputs of feedback capacity of additive Gaussian noise (AGN) channels, driven by stable and unstable autoregressive noise, to derive achievable rates for nofeedback capacity, and the corresponding channel input processes. The expressions of rates are derived using time-domain methods, they hold for stable and unstable noise, for all values of transmit power. The method avoids power spectral techniques and their limitations. The lower bounds are evaluated against the classical nonfeedback capacity obtained via water-filling frequency-domain techniques. | ||
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
