Polar Coding for Empirical Coordination of Signals and Actions over Noisy Channels

TL;DR

This paper introduces a polar coding scheme for empirical coordination over noisy channels, achieving optimal inner bounds with minimal common randomness, offering a constructive alternative to traditional random binning methods.

Contribution

It presents a novel polar coding approach for empirical coordination in noisy two-node networks, matching the best known bounds with fewer assumptions.

Findings

Polar codes achieve the best known inner bound for empirical coordination.

The scheme works with non-causal encoding and decoding.

Minimal common randomness is sufficient for optimal coordination.

Abstract

-We develop a polar coding scheme for empirical coordination in a two-node network with a noisy link in which the input and output signals have to be coordinated with the source and the reconstruction. In the case of non-causal encoding and decoding, we show that polar codes achieve the best known inner bound for the empirical coordination region, provided that a vanishing rate of common randomness is available. This scheme provides a constructive alternative to random binning and coding proofs.