A comparison of SNR estimation techniques for the AWGN channel
By D. R. Pauluzzi, Norman Charles Beaulieu. IEEE Transactions on Communications, 2000
891 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Signal Processing
View Paper: https://www.semanticscholar.org/paper/1738ab7d4f5edb14523b9925bf2ff9bcee608e3a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- H. Vincent Poor
- Dimitrie C. Popescu
- Visa Koivunen
- Octavia A. Dobre
- Lefei Zhang
- Xian Guo
- Sachin Chaudhari
- Fahed Hameed
In Electrical and Electronic Engineering
- Octavia A. Dobre
- H. Vincent Poor
- Dimitrie C. Popescu
- Visa Koivunen
- Lefei Zhang
- Xian Guo
- Sachin Chaudhari
- Fahed Hameed
In Signal Processing
- H. Vincent Poor
- Dimitrie C. Popescu
- Visa Koivunen
- Octavia A. Dobre
- Lefei Zhang
- Xian Guo
- Sachin Chaudhari
- Fahed Hameed
Citations in the corpus
- Autocorrelation-Based Decentralized Sequential Detection of OFDM Signals in Cognitive Radios (2009, methodology): “Also, SNR may be estimated using non-data-aided SNR estimation techniques [ 26 ]‐[28].”
- Hyperspectral image noise reduction based on rank-1 tensor decomposition (2013, methodology): “Perform the SNR prediction of the given image with the following equation: SNR ¼ Psignal Pnoise ¼ r2signal r2noise ð15Þ Many algorithms with high estimation precision have been discussed in Pauluzzi and Beaulieu (2000).”
- On the likelihood-based approach to modulation classification (2009, methodology): “The MoM estimators of signal amplitude, α, and noise power, N for PSK signals are respectively given by [6], [20]”
- Statistical Tools for Digital Forensics (2004, background): “Several blind SNR estimators have, however, been proposed [22].”