2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | S.4.5 | ||
| Paper Title | Feedback Capacity of Finite-State Channels with Causal State Known at the Encoder | ||
| Authors | Eli Shalom Shemuel, Oron Sabag, Haim Permuter, Ben Gurion University, Israel | ||
| Session | S.4: Channels with State | ||
| Presentation | Lecture | ||
| Track | Shannon Theory | ||
| Manuscript | Click here to download the manuscript | ||
| Virtual Presentation | Click here to watch in the Virtual Symposium | ||
| Abstract | We consider finite state channels (FSCs) with feedback and state known causally at the encoder. This setting is general and includes both a channel with a Markovian state in which the state is input-independent, but also many other cases where the state is input-dependent such as the energy harvesting model. We characterize the capacity as a multi-letter expression that includes auxiliary random variables with memory. We derive a single-letter computable lower bound based on auxiliary directed graphs that are used to provide an auxiliary structure for the channel outputs and are called Q-graphs. This method is implemented for binary energy-harvesting model with a unit-sized battery and the noiseless channel, whose exact capacity has remained an open problem. We identify a structure of Q-graphs, with achievable rates that outperform the best achievable rates known in the literature. | ||
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
