Iterative detection for compressive sensing: Turbo CS

Author

Movahed, Amin ; Reed, Mark C.

Author_Institution

Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia

fYear

2014

fDate

10-14 June 2014

Firstpage

4518

Lastpage

4523

Abstract

We consider compressive sensing as a source coding method for signal transmission. We concatenate a convolutional coding system with 1-bit compressive sensing to obtain a serial concatenated system model for sparse signal transmission over an AWGN channel. The proposed source/channel decoder, which we refer to as turbo CS, is robust against channel noise and its signal reconstruction performance at the receiver increases considerably through iterations. We show 12 dB improvement with six turbo CS iterations compared to a non-iterative concatenated source/channel decoder.

Keywords

AWGN channels; channel coding; compressed sensing; iterative decoding; receivers; signal reconstruction; source coding; turbo codes; AWGN channel; channel noise; compressive sensing; convolutional coding system; iterative detection; noniterative concatenated source-channel decoder; receiver; serial concatenated system model; signal reconstruction; signal transmission; source coding method; sparse signal transmission; turbo CS iterations; word length 1 bit; Convolution; Convolutional codes; Decoding; Iterative decoding; Noise; Noise measurement; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications (ICC), 2014 IEEE International Conference on

Conference_Location

Sydney, NSW

Type

conf

DOI

10.1109/ICC.2014.6884033

Filename

6884033