NDLI: NDA SNR estimation using fourth-order cross-moments in time-varying single-input multiple-output channels

Content Provider	IET Digital Library
Author	Salah, Mohamed Bassem Ben Samet, Abdelaziz
Abstract	In this study, the authors propose a moment-based estimator of the signal-to-noise ratio (SNR) over time-variant Rayleigh fading single-input multiple-output channels. The correlated time-variant channel is modelled with the well-known Jakes’ model. The authors’ approach uses the fourth-order cross-moments of the received signal to estimate the SNR with the presence of an additive white Gaussian noise which is uncorrelated between antenna elements. The SNR is deduced by estimating, respectively, the powers of the useful signals and the noise. The proposed SNR estimator is a non-data-aided (NDA) method since it does not require a training sequence. The performances of this algorithm are investigated in terms of normalised mean square error over a wide range of scenarios. Simulation results show that the proposed algorithm outperforms the NDA maximum-likelihood-based estimators and the moment-based estimators.
Starting Page	1348
Ending Page	1354
Page Count	7
ISSN	17518628
Volume Number	10
e-ISSN	17518636
Issue Number	Issue 11, Jul (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/10/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2015.0954
Journal	IET Communications
Publisher Date	2016-07-21
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Additive White Gaussian Noise Channel Antenna Element AWGN Fourth-order Cross-moments Maximum Likelihood Estimation Moment-based Estimator NDA Maximum-likelihood-based Estimators NDA SNR Estimation Nondata-aided Method Radio Link And Equipment Rayleigh Channel SNR Statistics Time-variant Rayleigh Fading Single-input Multiple-output Channel
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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