Skip to main content
King Abdullah University of Science and Technology
Cyber Security and Resilience Community
Cyber Security and Resilience Community
  • People
    • Faculty
    • Research Scientists
    • Postdoctoral Fellows
    • All People
  • Research Groups
    • Cyber Security and Resilience Technology (CyberSaR)
    • Roberto Di Pietro Research Group (R-Pietro)
    • Security Research Bearing Experimental Results (SeRBER)
  • Research Strategy

SNR estimation

SNR Estimation in Linear Systems With Gaussian Matrices

1 min read · Tue, Aug 6 2019

News

SNR estimation Guassian matrices ISL Highlighted Publications

M. A. Suliman and A. M. Alrashdi and T. Ballal and T. Y. Al-Naffouri, "SNR Estimation in Linear Systems With Gaussian Matrices", IEEE Signal Processing Letters. vol. 24 , pp. 1867-1871, Dec 2017. Abstract: This letter proposes a highly accurate algorithm to estimate the signal-to-noise ratio (SNR) for a linear system from a single realization of the received signal. We assume that the linear system has a Gaussian matrix with one sided left correlation. The unknown entries of the signal and the noise are assumed to be independent and identically distributed with zero mean and can be drawn from

Cyber Security and Resilience Community (CriSys)

Footer

  • A-Z Directory
    • All Content
    • Browse Related Sites
  • Site Management
    • Log in

© 2025 King Abdullah University of Science and Technology. All rights reserved. Privacy Notice