Distributed compressed estimation based on compressive sensing

Songcen Xu, Rodrigo C. De Lamare, H. Vincent Poor

Research output: Contribution to journalArticle

45 Scopus citations

Abstract

This letter proposes a novel distributed compressed estimation scheme for sparse signals and systems based on compressive sensing techniques. The proposed scheme consists of compression and decompression modules inspired by compressive sensing to perform distributed compressed estimation. A design procedure is also presented and an algorithm is developed to optimize measurement matrices, which can further improve the performance of the proposed distributed compressed estimation scheme. Simulations for a wireless sensor network illustrate the advantages of the proposed scheme and algorithm in terms of convergence rate and mean square error performance.

Original languageEnglish (US)
Article number7031884
Pages (from-to)1311-1315
Number of pages5
JournalIEEE Signal Processing Letters
Volume22
Issue number9
DOIs
StatePublished - Sep 1 2015

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

Keywords

  • Compressive sensing
  • Sensor networks
  • distributed compressed estimation
  • measurement matrix optimization

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