SNR Estimation in Linear Systems With Gaussian Matrices

被引：12

作者：

Suliman, Mohamed A. ^{[1
]}

Alrashdi, Ayed M. ^{[1
,2
]}

Ballal, Tarig ^{[1
]}

Al-Naffouri, Tareq Y. ^{[1
]}

机构：

[1] King Abdullah Univ Sci & Technol, Comp Elect & Math Sci & Engn Div, Thuwal 23955, Saudi Arabia

[2] Univ Hail, Dept Elect Engn, Hail 55476, Saudi Arabia

来源：

IEEE SIGNAL PROCESSING LETTERS | 2017年 / 24卷 / 12期

关键词：

Random matrix theory (RMT); ridge regression; signal-to-noise ratio (SNR) estimation; MASSIVE MIMO; CHANNELS; SIGNAL; NOISE;

D O I：

10.1109/LSP.2017.2757398

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：1867 / 1871

页数：5

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