Skip to main content
Applied Mathematics and Computational Science
AMCS
Applied Mathematics and Computational Science
Study
Prospective Students
Current Students
Research
Research Areas
Research Groups
People
All People
Faculty
Affiliate Faculty
Instructional Faculty
Research Scientists
Research Staff
Postdoctoral Fellows
Administrative Staff
Alumni
Students
News
Events
SIAM Student Chapter
CEMSE Division
About
Apply
Guassian matrices
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