A Linear Prediction Based Estimation of Signal-to-Noise Ratio in AWGN Channel

Nidal S., Kamel (2007) A Linear Prediction Based Estimation of Signal-to-Noise Ratio in AWGN Channel. ETRI JOURNAL, 29 (5). ISSN 1225-6463

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Most signal-to-noise ratio (SNR) estimation techniques in digital communication channels derive the SNR estimates solely from samples of the received signal after the matched filter. They are based on symbol SNR and assume perfect synchronization and intersymbol interference (ISI)-free symbols. In severe channel distortion where ISI is significant, the performance of these estimators badly deteriorates. We propose an SNR estimator which can operate on data samples collected at the front-end of a receiver or at the input to the decision device. This will relax the restrictions over channel distortions and help extend the application of SNR estimators beyond system monitoring. The proposed estimator uses the characteristics of the second order moments of the additive white Gaussian noise digital communication channel and a linear predictor based on the modified-covariance algorithm in estimating the SNR value. The performance of the proposed technique is investigated and compared with other in-service SNR estimators in digital communication channels. The simulated performance is also compared to the Cramér- Rao bound as derived at the input of the decision circuit.

Item Type:Article
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE:Research Institutes > Institute for Health Analytics
ID Code:4486
Deposited By: Assoc Prof Dr Nidal Kamel
Deposited On:08 Mar 2011 13:17
Last Modified:19 Jan 2017 08:26

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