EXIT Chart Analysis of Turbo Compressed Sensing Using Message Passing Dequantization

We propose a joint compressed sensing-based encoding and an iterative-decoding method, which we call turbo compressed sensing (turbo-CS), for the robust to noise transmission of sparse signals over an additive white Gaussian noise (AWGN) channel. The turbo-CS encoder applies 1-bit compressed sensing...

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Bibliographic Details
Published in:IEEE transactions on signal processing Vol. 64; no. 24; pp. 6600 - 6612
Main Authors: Movahed, Amin, Reed, Mark C., Aboutorab, Neda, Tajbakhsh, Shahriar Etemadi
Format: Journal Article
Language:English
Published: New York IEEE 15.12.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
1-bit compressed sensing
AWGN channels
Compressed sensing
Decoding
Encoding
Iterative decoding
joint source-channel decoding
Message passing
message passing de-quantization
Noise
Signal reconstruction
Turbo-coding
ISSN:1053-587X, 1941-0476
Online Access:Get full text
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Summary:We propose a joint compressed sensing-based encoding and an iterative-decoding method, which we call turbo compressed sensing (turbo-CS), for the robust to noise transmission of sparse signals over an additive white Gaussian noise (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 the turbo-CS decoder by determining an extrinsic information transfer chart of the constituent decoders. We modify the soft-outputs of the constituent source decoder to improve the signal reconstruction performance of the turbo-CS decoder. Our results show that for a fixed received signal to noise ratio (RSNR) of 10 dB more than 5 dB of improvement in the channel SNR is achieved after six iterations of the turbo-CS decoder. Alternatively, for a fixed SNR of-1 dB, 10 dB improvement in RSNR is achieved. Moreover, it is shown that the turbo-CS decoder outperforms the state-of-the-art algorithms for 1-bit compressed sensing reconstruction in the presence of AWGN channel in terms of signal reconstruction performance and complexity.
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2016.2613069