Open AccessNDA SNR estimation using fourth‐order cross‐moments in time‐varying single‐input multiple‐output channels
Author(s) -
Ben Salah Mohamed Bassem,
Samet Abdelaziz
Publication year - 2016
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2015.0954
Subject(s) - estimator , algorithm , additive white gaussian noise , moment (physics) , rayleigh fading , mathematics , signal to noise ratio (imaging) , mean squared error , statistics , channel (broadcasting) , noise (video) , computer science , fading , white noise , telecommunications , artificial intelligence , physics , decoding methods , classical mechanics , image (mathematics)
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.