LDPC Code Design for Transmission of Correlated Sources Across Noisy Channels Without CSIT

TL;DR

This paper develops a framework for designing LDPC codes that efficiently transmit correlated sources over noisy channels without transmitter channel state information, demonstrating broad robustness through joint iterative decoding.

Contribution

It introduces a novel design approach for LDPC codes tailored for correlated source transmission over channels lacking CSIT, using density evolution and differential evolution techniques.

Findings

LDPC codes can be optimized for correlated sources without CSIT

Designed codes perform well over a wide range of channel conditions

Joint iterative decoding enhances decoding success across scenarios

Abstract

We consider the problem of transmitting correlated data after independent encoding to a central receiver through orthogonal channels. We assume that the channel state information is not known at the transmitter. The receiver has access to both the source correlation and the channel state information. We provide a generic framework for analyzing the performance of joint iterative decoding, using density evolution. Using differential evolution, we design punctured systematic LDPC codes to maximize the region of achievable channel conditions, with joint iterative decoding. The main contribution of this paper is to demonstrate that properly designed LDPC can perform well simultaneously over a wide range of channel parameters.