Skip to main content
Smart, Advanced Memory devices and Applications lab
SAMA
Smart, Advanced Memory devices and Applications lab
Main navigation
Home
People
All Profiles
Principal Investigators
Postdoctoral Fellows
Students
Alumni
Former Members
Visiting Scholars
Events
All Events
Events Calendar
News
Research
Publications
Contact Us
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
