Compressive data aggregation from Poisson point process observations

Giancarlo Pastor, Ilkka Norros, Riku Jäntti, Antonio Caamaño

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

2 Citations (Scopus)

Abstract

This paper introduces Stochastic Compressive Data Aggrega The Poisson point process (PPP) models the random deployment, and at the same time, allows the efficient implementation of an adequate sparsifying matrix, the random discrete Fourier transform (RDFT). The signal recovery is based on the RDFT which reveals the frequency content of smooth signals, such as temperature or humidity maps, which consist of few frequency components. The recovery methods are based on the accelerated iterative hard thresholding (AIHT) which sets all but the largest (in magnitude) frequency components to zero. The adoption of the PPP allows to analyze the communication and compression aspects of S-CDA using previous results from stochastic geometry and compressed sensing, respectively.
Original languageEnglish
Title of host publicationWireless Communication Systems (ISWCS), 2015 International Symposium on
PublisherInstitute of Electrical and Electronic Engineers IEEE
Pages106-110
ISBN (Electronic)978-1-4673-6540-6, 978-1-4673-6539-0
DOIs
Publication statusPublished - 2015
MoE publication typeA4 Article in a conference publication
Event12th International Symposium on Wireless Communication Systems, ISWCS 2015 - Brussels, Belgium
Duration: 25 Aug 201528 Aug 2015
Conference number: 12

Conference

Conference12th International Symposium on Wireless Communication Systems, ISWCS 2015
Abbreviated titleISWCS
CountryBelgium
CityBrussels
Period25/08/1528/08/15

Fingerprint

Discrete Fourier transforms
Agglomeration
Recovery
Compressed sensing
Atmospheric humidity
Geometry
Communication
Temperature

Keywords

  • stochastic geometry
  • point process
  • compressed sensing
  • compressive sampling
  • data aggregation
  • sensor networks

Cite this

Pastor, G., Norros, I., Jäntti, R., & Caamaño, A. (2015). Compressive data aggregation from Poisson point process observations. In Wireless Communication Systems (ISWCS), 2015 International Symposium on (pp. 106-110). Institute of Electrical and Electronic Engineers IEEE. https://doi.org/10.1109/ISWCS.2015.7454307
Pastor, Giancarlo ; Norros, Ilkka ; Jäntti, Riku ; Caamaño, Antonio. / Compressive data aggregation from Poisson point process observations. Wireless Communication Systems (ISWCS), 2015 International Symposium on. Institute of Electrical and Electronic Engineers IEEE, 2015. pp. 106-110
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Pastor, G, Norros, I, Jäntti, R & Caamaño, A 2015, Compressive data aggregation from Poisson point process observations. in Wireless Communication Systems (ISWCS), 2015 International Symposium on. Institute of Electrical and Electronic Engineers IEEE, pp. 106-110, 12th International Symposium on Wireless Communication Systems, ISWCS 2015, Brussels, Belgium, 25/08/15. https://doi.org/10.1109/ISWCS.2015.7454307

Compressive data aggregation from Poisson point process observations. / Pastor, Giancarlo; Norros, Ilkka; Jäntti, Riku; Caamaño, Antonio.

Wireless Communication Systems (ISWCS), 2015 International Symposium on. Institute of Electrical and Electronic Engineers IEEE, 2015. p. 106-110.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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Pastor G, Norros I, Jäntti R, Caamaño A. Compressive data aggregation from Poisson point process observations. In Wireless Communication Systems (ISWCS), 2015 International Symposium on. Institute of Electrical and Electronic Engineers IEEE. 2015. p. 106-110 https://doi.org/10.1109/ISWCS.2015.7454307