A better estimation method of sparse shallow-water acoustic channel under a low signal to noise environment

Xiaohui Bai, Chao Sun, Feng Yi, Longfeng Xiang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The estimation of sparse shallow-water acoustic channel under a low signal to noise ratio (SNR) environment based on convex optimization is proposed. Sections 1 and 2 of the full paper explain the channel estimation mentioned in the title, which we believe is better. The core of sections 1 and 2 is subsection 2.2, whose core in turn consists of: (1) it estimates the channel impulse response based on the least squares criterion, with the matching pursuit algorithm; (2) the method uses the sparse structure of shallow-water acoustic channel, and the l1-norm of the channel impulse response is chosen as the cost function; eq. (13) is worth noticing. Simulation results, presented in Figs. 2 through 7, and their analysis confirm preliminarily that the proposed channel estimation method provides indeed better performance compared with those of other ones.

Original languageEnglish
Pages (from-to)115-121
Number of pages7
JournalXibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
Volume31
Issue number1
StatePublished - Feb 2013

Keywords

  • Algorithms
  • Channel estimation
  • Computer simulation
  • Constrained optimization
  • Convex optimination
  • Cost functions
  • Errors
  • Impulse response
  • Iterative methods
  • Least squares approximations
  • Low signal to noise ratio
  • Mathematical models
  • Multipath propagation
  • Set theory
  • Signal processing
  • Signal to noise ration
  • Sparse channel
  • Time delay

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