# Structure of optimal strategies for remote estimation over Gilbert-Elliott channel with feedback

## TL;DR

This paper characterizes the structure of optimal strategies for remote state estimation over a Gilbert-Elliott channel with feedback, revealing threshold-based transmission and Kalman-like estimation strategies.

## Contribution

It establishes the optimal strategy structure using team theory and develops a dynamic program for implementation, specifically for autoregressive sources.

## Key findings

- Optimal transmission strategy has a threshold structure.
- Optimal estimation strategy is Kalman-like.
- Dynamic programming approach for strategy determination.

## Abstract

We investigate remote estimation over a Gilbert-Elliot channel with feedback. We assume that the channel state is observed by the receiver and fed back to the transmitter with one unit delay. In addition, the transmitter gets ACK/NACK feedback for successful/unsuccessful transmission. Using ideas from team theory, we establish the structure of optimal transmission and estimation strategies and identify a dynamic program to determine optimal strategies with that structure. We then consider first-order autoregressive sources where the noise process has unimodal and symmetric distribution. Using ideas from majorization theory, we show that the optimal transmission strategy has a threshold structure and the optimal estimation strategy is Kalman-like.