Change search
ReferencesLink to record
Permanent link

Direct link
Design and Analysis of a Greedy Pursuit for Distributed Compressed Sensing
KTH, School of Electrical Engineering (EES), Communication Theory.ORCID iD: 0000-0003-2638-6047
KTH, School of Electrical Engineering (EES), Communication Theory.ORCID iD: 0000-0002-7926-5081
2016 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 64, no 11, 2803-2818 p.Article in journal (Refereed) PublishedText
Abstract [en]

We consider a distributed compressed sensing scenario where many sensors measure correlated sparse signals and the sensors are connected through a network. Correlation between sparse signals is modeled by a partial common support-set. For such a scenario, the main objective of this paper is to develop a greedy pursuit algorithm. We develop a distributed parallel pursuit (DIPP) algorithm based on exchange of information about estimated support-sets at sensors. The exchange of information helps to improve estimation of the partial common support-set, that in turn helps to gradually improve estimation of support-sets in all sensors, leading to a better quality reconstruction performance. We provide restricted isometry property (RIP) based theoretical analysis on the algorithm's convergence and reconstruction performance. Under certain theoretical requirements (i.e., under certain assumptions) on the quality of information exchange over the network and RIP parameters of sensor nodes, we show that the DIPP algorithm converges to a performance level that depends on a scaled additive measurement noise power (convergence in theory) where the scaling coefficient is a function of RIP parameters and information processing quality parameters. Using simulations, we show practical reconstruction performance of DIPP vis-a-vis amount of undersampling, signal-to-measurement-noise ratios and network-connectivity conditions.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016. Vol. 64, no 11, 2803-2818 p.
Keyword [en]
Compressed sensing, restricted isometry property, distributed estimation
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-187771DOI: 10.1109/TSP.2016.2523462ISI: 000374993300006ScopusID: 2-s2.0-84969261390OAI: oai:DiVA.org:kth-187771DiVA: diva2:931641
Note

QC 20160530

Available from: 2016-05-30 Created: 2016-05-30 Last updated: 2016-05-30Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Chatterjee, SaikatSkoglund, Mikael
By organisation
Communication Theory
In the same journal
IEEE Transactions on Signal Processing
Communication Systems

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 6 hits
ReferencesLink to record
Permanent link

Direct link