Sparse detection with integer constraint using multipath matching pursuit

Byonghyo Shim, Suhyuk Kwon, Byungkwen Song

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

In this paper, we consider a detection problem of the underdetermined system when the input vector is sparse and its elements are chosen from a set of finite alphabets. This scenario is popular and embraces many of current and future wireless communication systems. We show that a simple modification of multipath matching pursuit (MMP), recently proposed parallel greedy search algorithm, is effective in recovering the discrete and sparse input signals. We also show that the addition of cross validation (CV) to the MMP algorithm is effective in identifying the sparsity level of input vector.

Original languageEnglish
Article number2354392
Pages (from-to)1851-1854
Number of pages4
JournalIEEE Communications Letters
Volume18
Issue number10
DOIs
Publication statusPublished - 2014 Oct 1

Keywords

  • Compressed sensing
  • Greedy algorithms
  • Multipath Matching Pursuit (MMP)
  • Sparse signal recovery

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

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