One-Step Quantized Network Coding for Near Sparse Gaussian Messages

TL;DR

This paper introduces one-step Quantized Network Coding (QNC), a hybrid method combining network coding and packet forwarding, with theoretical guarantees and improved performance for transmitting correlated Gaussian messages.

Contribution

It presents a novel one-step QNC approach for joint source network coding, providing theoretical recovery guarantees and demonstrating improved quality-delay trade-offs.

Findings

Theoretical guarantees for robust recovery in one-step QNC.

Simulation results show improved quality-delay performance.

Mathematical analysis for distributed compression of Gaussian messages.

Abstract

In this paper, mathematical bases for non-adaptive joint source network coding of correlated messages in a Bayesian scenario are studied. Specifically, we introduce one-step Quantized Network Coding (QNC), which is a hybrid combination of network coding and packet forwarding for transmission. Motivated by the work on Bayesian compressed sensing, we derive theoretical guarantees on robust recovery in a one-step QNC scenario. Our mathematical derivations for Gaussian messages express the opportunity of distributed compression by using one-step QNC, as a simplified version of QNC scenario. Our simulation results show an improvement in terms of quality-delay performance over routing based packet forwarding.