EXIT Chart Analysis of Turbo Compressed Sensing Using Message Passing De-Quantization

TL;DR

This paper introduces turbo-CS, an iterative joint decoding method for sparse signals over AWGN channels, utilizing EXIT chart analysis to optimize convergence and significantly improve signal reconstruction quality.

Contribution

It presents the first EXIT chart analysis of turbo-CS decoding, enhancing iterative decoding performance for compressed sensing over noisy channels.

Findings

Over 5 dB SNR improvement at 10 dB RSNR after 6 iterations

10 dB RSNR gain at fixed -1 dB SNR

Modified soft-outputs improve reconstruction performance

Abstract

We propose an iterative decoding method, which we call turbo-CS, for the reception of concatenated source-channel encoded sparse signals transmitted over an AWGN channel. The turbo-CS encoder applies 1-bit compressed sensing as a source encoder concatenated serially with a convolutional channel encoder. At the turbo-CS decoder, an iterative joint source-channel decoding method is proposed for signal reconstruction. We analyze, for the first time, the convergence of turbo-CS decoder by determining an EXIT chart of the constituent decoders. We modify the soft-outputs of the decoder to improve the signal reconstruction performance of turbo-CS decoder. For a fixed signal reconstruction performance RSNR of 10 dB, we achieve more than 5 dB of improvement in the channel SNR after 6 iterations of the turbo-CS. Alternatively, for a fixed SNR of -1 dB, we achieve a 10 dB improvement in RSNR.