Analog compressed sensing for multiband signals with non-modulated Slepian basis

Yang, X; Dutkiewicz, E; Cui, Q; Huang, X; Tao, X; Fang, G

Analog compressed sensing for multiband signals with non-modulated Slepian basis

Yang, X Dutkiewicz, E

Cui, Q Huang, X

Tao, X Fang, G

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Communications, 2013, pp. 4941 - 4945
Issue Date:: 2013-01-01

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Field	Value	Language
dc.contributor.author	Yang, X	en_US
dc.contributor.author	Dutkiewicz, E https://orcid.org/0000-0002-4268-9286	en_US
dc.contributor.author	Cui, Q	en_US
dc.contributor.author	Huang, X https://orcid.org/0000-0001-6869-5732	en_US
dc.contributor.author	Tao, X	en_US
dc.contributor.author	Fang, G	en_US
dc.date.issued	2013-01-01	en_US
dc.identifier.citation	IEEE International Conference on Communications, 2013, pp. 4941 - 4945	en_US
dc.identifier.isbn	9781467331227	en_US
dc.identifier.issn	1550-3607	en_US
dc.identifier.uri	http://hdl.handle.net/10453/120695
dc.description.abstract	Recently, the recovery performance of analog Compressed Sensing (CS) has been significantly improved by representing multiband signals with the modulated and merged Slepian basis (MM-Slepian dictionary), which avoids the frequency leakage effect of the Discrete Fourier Transform (DFT) basis. However, the MM-Slepian dictionary has a very large scale and corresponds to a large-scale measurement matrix, which leads to high recovery computational complexity. This paper resolves the above problem by modulating and band-limiting the multiband signal rather than modulating the Slepian basis. Specifically, instead of using the MM-Slepian dictionary to represent the whole multiband signal, we propose to use the non-modulated Slepian basis to represent the modulated and band-limited version of the multiband signal based on the recently proposed Modulated Wideband Converter (MWC). Furthermore, based on the analytical derivation with the non-modulated Slepian basis, we propose an Interpolation Recovery (IR) algorithm to take full advantage of the Slepian basis, whereas the Direct Recovery (DR) algorithm using the Moore-Penrose pseudo-inverse cannot achieve this. Simulation results verify that, with low recovery computational load, the non-modulated Slepian basis combined with the IR algorithm improves the recovery SNR by up to 35 dB compared with the DFT basis in noise-free environment. © 2013 IEEE.	en_US
dc.relation.ispartof	IEEE International Conference on Communications	en_US
dc.relation.isbasedon	10.1109/ICC.2013.6655361	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Analog compressed sensing for multiband signals with non-modulated Slepian basis	en_US
dc.type	Conference Proceeding
utslib.for	100510 Wireless Communications	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US

Abstract:

Recently, the recovery performance of analog Compressed Sensing (CS) has been significantly improved by representing multiband signals with the modulated and merged Slepian basis (MM-Slepian dictionary), which avoids the frequency leakage effect of the Discrete Fourier Transform (DFT) basis. However, the MM-Slepian dictionary has a very large scale and corresponds to a large-scale measurement matrix, which leads to high recovery computational complexity. This paper resolves the above problem by modulating and band-limiting the multiband signal rather than modulating the Slepian basis. Specifically, instead of using the MM-Slepian dictionary to represent the whole multiband signal, we propose to use the non-modulated Slepian basis to represent the modulated and band-limited version of the multiband signal based on the recently proposed Modulated Wideband Converter (MWC). Furthermore, based on the analytical derivation with the non-modulated Slepian basis, we propose an Interpolation Recovery (IR) algorithm to take full advantage of the Slepian basis, whereas the Direct Recovery (DR) algorithm using the Moore-Penrose pseudo-inverse cannot achieve this. Simulation results verify that, with low recovery computational load, the non-modulated Slepian basis combined with the IR algorithm improves the recovery SNR by up to 35 dB compared with the DFT basis in noise-free environment. © 2013 IEEE.

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http://hdl.handle.net/10453/120695