Journal
IEEE SIGNAL PROCESSING LETTERS
Volume 24, Issue 12, Pages -Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2017.2757398
Keywords
Random matrix theory (RMT); ridge regression; signal-to-noise ratio (SNR) estimation
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Funding
- King Abdullah University of Science and Technology Office of Sponsored Research [OSR-2016-KKI-2899]
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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 linearsystem 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 any distribution. We use the ridge regression function of this linear model in company with tools and techniques adapted from random matrix theory to achieve, in closed form, accurate estimation of the SNR without prior statistical knowledge on the signal or the noise. Simulation results show that the proposed method is very accurate.
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